diff --git a/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp b/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
index b6314e4..9a17172 100644
--- a/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
+++ b/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
@@ -16,6 +16,7 @@ using json = nlohmann::json;
 #include "rpt_msgs/msg/poses.hpp"
 #include "/RapidPoseTriangulation/rpt/camera.hpp"
 #include "/RapidPoseTriangulation/rpt/interface.hpp"
+#include "/RapidPoseTriangulation/rpt/tracker.hpp"
 
 // =================================================================================================
 
@@ -36,9 +37,14 @@ static const std::string pose_in_topic = "/poses/{}";
 static const std::string cam_info_topic = "/{}/calibration";
 static const std::string pose_out_topic = "/poses/humans3d";
 
-static const float min_match_score = 0.92;
+static const float min_match_score = 0.94;
 static const size_t min_group_size = 1;
 
+static const bool use_tracking = true;
+static const float max_movement_speed = 2.0 * 1.5;
+static const float cam_fps = 50;
+static const float max_track_distance = 0.3 + max_movement_speed / cam_fps;
+
 static const std::array<std::array<float, 3>, 2> roomparams = {{
     {4.0, 5.0, 2.2},
     {1.0, 0.0, 1.1},
@@ -59,9 +65,11 @@ public:
         this->joint_names = {};
         this->all_poses_set.resize(cam_ids.size(), false);
 
-        // Load 3D model
+        // Load 3D models
         tri_model = std::make_unique<Triangulator>(
             min_match_score, min_group_size);
+        pose_tracker = std::make_unique<PoseTracker>(
+            max_movement_speed, max_track_distance);
 
         // QoS
         rclcpp::QoS qos_profile(1);
@@ -113,6 +121,7 @@ private:
     rclcpp::Publisher<rpt_msgs::msg::Poses>::SharedPtr pose_pub_;
 
     std::unique_ptr<Triangulator> tri_model;
+    std::unique_ptr<PoseTracker> pose_tracker;
     std::vector<Camera> all_cameras;
     std::mutex cams_mutex, pose_mutex, model_mutex;
 
@@ -230,11 +239,32 @@ void Rpt3DWrapperNode::call_model()
     // Since the prediction is very fast, parallel callback threads only need to wait a short time
     cams_mutex.lock();
     pose_mutex.lock();
-    const auto valid_poses = tri_model->triangulate_poses(
+    const auto poses_3d = tri_model->triangulate_poses(
         all_poses, all_cameras, roomparams, joint_names);
 
     double min_ts = *std::min_element(all_timestamps.begin(), all_timestamps.end());
     this->all_poses_set = std::vector<bool>(cam_ids.size(), false);
+
+    std::vector<std::vector<std::array<float, 4>>> valid_poses;
+    std::vector<size_t> track_ids;
+    if (use_tracking)
+    {
+        auto pose_tracks = pose_tracker->track_poses(poses_3d, joint_names, min_ts);
+        std::vector<std::vector<std::array<float, 4>>> poses_3d_refined;
+    for (size_t j = 0; j < pose_tracks.size(); j++)
+    {
+        auto &pose = std::get<1>(pose_tracks[j]);
+        poses_3d_refined.push_back(pose);
+        auto &track_id = std::get<0>(pose_tracks[j]);
+        track_ids.push_back(track_id);
+    }
+        valid_poses = std::move(poses_3d_refined);
+    }
+    else
+    {
+        valid_poses = std::move(poses_3d);
+        track_ids = {};
+    }
     pose_mutex.unlock();
     cams_mutex.unlock();
 
@@ -267,6 +297,7 @@ void Rpt3DWrapperNode::call_model()
         }
     }
     pose_msg.joint_names = joint_names;
+    jdata["track_ids"] = track_ids;
     pose_msg.extra_data = jdata.dump();
     pose_pub_->publish(pose_msg);
 
diff --git a/media/RESULTS.md b/media/RESULTS.md
index e7a6591..8f04b3b 100644
--- a/media/RESULTS.md
+++ b/media/RESULTS.md
@@ -7,26 +7,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0210844,
-  "demosaicing": 0.000613385,
-  "avg_time_2d": 0.00826702,
-  "avg_time_3d": 3.67275e-05,
-  "fps": 112.144
+  "img_loading": 0.0209625,
+  "demosaicing": 0.000622594,
+  "avg_time_2d": 0.00825327,
+  "avg_time_3d": 3.69146e-05,
+  "time_tracks": 4.75515e-07,
+  "fps": 112.192
 }
 {
   "triangulator_calls": 600,
-  "init_time": 2.66098e-06,
-  "undistort_time": 3.72397e-06,
-  "project_time": 7.0124e-07,
-  "match_time": 1.19658e-06,
-  "pairs_time": 2.10813e-07,
-  "pair_scoring_time": 5.9247e-06,
-  "grouping_time": 1.35449e-06,
-  "full_time": 7.78258e-06,
-  "merge_time": 3.15914e-06,
-  "post_time": 4.86037e-06,
-  "convert_time": 5.47233e-08,
-  "total_time": 3.18622e-05
+  "init_time": 2.68551e-06,
+  "undistort_time": 3.71778e-06,
+  "project_time": 6.96477e-07,
+  "match_time": 1.27031e-06,
+  "pairs_time": 2.0875e-07,
+  "pair_scoring_time": 6.06621e-06,
+  "grouping_time": 1.3693e-06,
+  "full_time": 7.96046e-06,
+  "merge_time": 3.21646e-06,
+  "post_time": 4.74177e-06,
+  "convert_time": 6.763e-08,
+  "total_time": 3.22448e-05
 }
 {
   "person_nums": {
@@ -45,10 +46,10 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 600,
-    "mean": 0.060496,
-    "median": 0.053051,
-    "std": 0.028242,
-    "sem": 0.001154,
+    "mean": 0.060535,
+    "median": 0.053044,
+    "std": 0.028266,
+    "sem": 0.001155,
     "min": 0.036391,
     "max": 0.191685,
     "recall-0.025": 0.0,
@@ -59,9 +60,9 @@ Results of the model in various experiments on different datasets. \
     "recall-0.5": 1.0,
     "num_labels": 600,
     "ap-0.025": 0.0,
-    "ap-0.05": 0.189462,
-    "ap-0.1": 0.906596,
-    "ap-0.15": 0.914939,
+    "ap-0.05": 0.189774,
+    "ap-0.1": 0.906441,
+    "ap-0.15": 0.914804,
     "ap-0.25": 1.0,
     "ap-0.5": 1.0
   },
@@ -147,15 +148,15 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
     "count": 600,
-    "mean": 0.03991,
+    "mean": 0.03981,
     "median": 0.022309,
-    "std": 0.04422,
-    "sem": 0.001807,
+    "std": 0.044042,
+    "sem": 0.0018,
     "min": 0.003241,
     "max": 0.252773,
     "recall-0.025": 0.548333,
     "recall-0.05": 0.761667,
-    "recall-0.1": 0.91,
+    "recall-0.1": 0.911667,
     "recall-0.15": 0.928333,
     "recall-0.25": 0.998333,
     "recall-0.5": 1.0,
@@ -243,17 +244,17 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_left": {
     "count": 598,
-    "mean": 0.088855,
-    "median": 0.082483,
-    "std": 0.030683,
-    "sem": 0.001256,
-    "min": 0.046704,
+    "mean": 0.089465,
+    "median": 0.08257,
+    "std": 0.031872,
+    "sem": 0.001304,
+    "min": 0.049959,
     "max": 0.353694,
     "recall-0.025": 0.0,
-    "recall-0.05": 0.003333,
-    "recall-0.1": 0.875,
-    "recall-0.15": 0.943333,
-    "recall-0.25": 0.993333,
+    "recall-0.05": 0.001667,
+    "recall-0.1": 0.871667,
+    "recall-0.15": 0.94,
+    "recall-0.25": 0.991667,
     "recall-0.5": 0.996667,
     "num_labels": 600
   },
@@ -277,8 +278,8 @@ Results of the model in various experiments on different datasets. \
     "num_labels": 7800,
     "recall-0.025": 0.18833,
     "recall-0.05": 0.50474,
-    "recall-0.1": 0.88218,
-    "recall-0.15": 0.93577,
+    "recall-0.1": 0.88205,
+    "recall-0.15": 0.93564,
     "recall-0.25": 0.99564,
     "recall-0.5": 0.99923
   }
@@ -294,63 +295,64 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0415539,
-  "demosaicing": 0.000729576,
-  "avg_time_2d": 0.0147618,
-  "avg_time_3d": 0.000120587,
-  "fps": 64.0536
+  "img_loading": 0.0410789,
+  "demosaicing": 0.000730512,
+  "avg_time_2d": 0.0147695,
+  "avg_time_3d": 0.000120724,
+  "time_tracks": 9.84223e-07,
+  "fps": 64.0135
 }
 {
   "triangulator_calls": 301,
-  "init_time": 2.88489e-06,
-  "undistort_time": 1.4084e-05,
-  "project_time": 2.09862e-06,
-  "match_time": 8.48508e-06,
-  "pairs_time": 3.70267e-06,
-  "pair_scoring_time": 2.68451e-05,
-  "grouping_time": 6.3545e-06,
-  "full_time": 2.70454e-05,
-  "merge_time": 1.16283e-05,
-  "post_time": 7.58572e-06,
-  "convert_time": 1.18993e-07,
-  "total_time": 0.000111068
+  "init_time": 3.06285e-06,
+  "undistort_time": 1.40894e-05,
+  "project_time": 2.08899e-06,
+  "match_time": 8.13459e-06,
+  "pairs_time": 4.04345e-06,
+  "pair_scoring_time": 2.6331e-05,
+  "grouping_time": 6.48039e-06,
+  "full_time": 2.68403e-05,
+  "merge_time": 1.17703e-05,
+  "post_time": 7.74161e-06,
+  "convert_time": 1.379e-07,
+  "total_time": 0.000110955
 }
 {
   "person_nums": {
     "total_frames": 301,
     "total_labels": 477,
-    "total_preds": 824,
+    "total_preds": 839,
     "considered_empty": 0,
     "valid_preds": 477,
-    "invalid_preds": 347,
+    "invalid_preds": 362,
     "missing": 0,
-    "invalid_fraction": 0.42112,
-    "precision": 0.57888,
+    "invalid_fraction": 0.43147,
+    "precision": 0.56853,
     "recall": 1.0,
-    "f1": 0.73328,
-    "non_empty": 824
+    "f1": 0.72492,
+    "non_empty": 839
   },
   "mpjpe": {
     "count": 477,
-    "mean": 0.047573,
-    "median": 0.042506,
-    "std": 0.014988,
-    "sem": 0.000687,
+    "mean": 0.047475,
+    "median": 0.042505,
+    "std": 0.01481,
+    "sem": 0.000679,
     "min": 0.028778,
-    "max": 0.118939,
+    "max": 0.107262,
     "recall-0.025": 0.0,
-    "recall-0.05": 0.72327,
-    "recall-0.1": 0.987421,
+    "recall-0.05": 0.725367,
+    "recall-0.1": 0.985325,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 477,
     "ap-0.025": 0.0,
-    "ap-0.05": 0.45546,
-    "ap-0.1": 0.752725,
-    "ap-0.15": 0.761685,
-    "ap-0.25": 0.761685,
-    "ap-0.5": 0.761685
+    "ap-0.05": 0.459533,
+    "ap-0.1": 0.75171,
+    "ap-0.15": 0.762056,
+    "ap-0.25": 0.762056,
+    "ap-0.5": 0.762056
   },
   "head": {
     "count": 477,
@@ -402,17 +404,17 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_left": {
     "count": 477,
-    "mean": 0.04052,
+    "mean": 0.039987,
     "median": 0.03197,
-    "std": 0.028831,
-    "sem": 0.001321,
+    "std": 0.026065,
+    "sem": 0.001195,
     "min": 0.003618,
-    "max": 0.309844,
+    "max": 0.145663,
     "recall-0.025": 0.312369,
     "recall-0.05": 0.756813,
-    "recall-0.1": 0.953878,
-    "recall-0.15": 0.997904,
-    "recall-0.25": 0.997904,
+    "recall-0.1": 0.955975,
+    "recall-0.15": 1.0,
+    "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 477
   },
@@ -434,33 +436,33 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
     "count": 477,
-    "mean": 0.059302,
-    "median": 0.054034,
-    "std": 0.038636,
-    "sem": 0.001771,
+    "mean": 0.05886,
+    "median": 0.053989,
+    "std": 0.037537,
+    "sem": 0.001721,
     "min": 0.00164,
     "max": 0.32449,
     "recall-0.025": 0.146751,
-    "recall-0.05": 0.412998,
-    "recall-0.1": 0.909853,
-    "recall-0.15": 0.964361,
-    "recall-0.25": 0.991614,
+    "recall-0.05": 0.415094,
+    "recall-0.1": 0.91195,
+    "recall-0.15": 0.966457,
+    "recall-0.25": 0.993711,
     "recall-0.5": 1.0,
     "num_labels": 477
   },
   "wrist_right": {
     "count": 477,
-    "mean": 0.05829,
+    "mean": 0.057792,
     "median": 0.053472,
-    "std": 0.034177,
-    "sem": 0.001566,
+    "std": 0.031027,
+    "sem": 0.001422,
     "min": 0.008622,
-    "max": 0.382984,
+    "max": 0.208627,
     "recall-0.025": 0.113208,
     "recall-0.05": 0.440252,
     "recall-0.1": 0.90566,
-    "recall-0.15": 0.981132,
-    "recall-0.25": 0.997904,
+    "recall-0.15": 0.983229,
+    "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 477
   },
@@ -546,17 +548,17 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_right": {
     "count": 477,
-    "mean": 0.040896,
+    "mean": 0.041098,
     "median": 0.030845,
-    "std": 0.037576,
-    "sem": 0.001722,
+    "std": 0.038414,
+    "sem": 0.001761,
     "min": 0.003445,
     "max": 0.28852,
     "recall-0.025": 0.301887,
     "recall-0.05": 0.807128,
     "recall-0.1": 0.930818,
-    "recall-0.15": 0.968553,
-    "recall-0.25": 0.997904,
+    "recall-0.15": 0.966457,
+    "recall-0.25": 0.995807,
     "recall-0.5": 1.0,
     "num_labels": 477
   },
@@ -564,16 +566,16 @@ Results of the model in various experiments on different datasets. \
     "num_labels": 6201,
     "recall-0.025": 0.21609,
     "recall-0.05": 0.62329,
-    "recall-0.1": 0.94291,
-    "recall-0.15": 0.9871,
-    "recall-0.25": 0.99871,
+    "recall-0.1": 0.94356,
+    "recall-0.15": 0.98742,
+    "recall-0.25": 0.99903,
     "recall-0.5": 1.0
   }
 }
 {
   "total_parts": 6678,
-  "correct_parts": 6623,
-  "pcp": 0.991764
+  "correct_parts": 6625,
+  "pcp": 0.992063
 }
 {
   "total_parts": {
@@ -584,15 +586,15 @@ Results of the model in various experiments on different datasets. \
   },
   "correct_parts": {
     "1": 2790,
-    "3": 1608,
-    "2": 369,
-    "sum": 4767
+    "3": 1610,
+    "2": 370,
+    "sum": 4770
   },
   "pcp": {
     "1": 1.0,
-    "3": 0.998758,
-    "2": 0.997297,
-    "avg": 0.998685
+    "3": 1.0,
+    "2": 1.0,
+    "avg": 1.0
   }
 }
 ```
@@ -601,63 +603,64 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.00473995,
-  "demosaicing": 0.000176621,
-  "avg_time_2d": 0.0069666,
-  "avg_time_3d": 3.95759e-05,
-  "fps": 139.222
+  "img_loading": 0.00474583,
+  "demosaicing": 0.000182246,
+  "avg_time_2d": 0.006994,
+  "avg_time_3d": 4.00988e-05,
+  "time_tracks": 7.41094e-07,
+  "fps": 138.56
 }
 {
   "triangulator_calls": 222,
-  "init_time": 2.30386e-06,
-  "undistort_time": 5.79863e-06,
-  "project_time": 1.05762e-06,
-  "match_time": 2.8811e-06,
-  "pairs_time": 4.73671e-07,
-  "pair_scoring_time": 5.02461e-06,
-  "grouping_time": 1.36539e-06,
-  "full_time": 6.40501e-06,
-  "merge_time": 3.01859e-06,
-  "post_time": 6.25936e-06,
-  "convert_time": 1.01095e-07,
-  "total_time": 3.49216e-05
+  "init_time": 2.40937e-06,
+  "undistort_time": 5.79809e-06,
+  "project_time": 1.04741e-06,
+  "match_time": 2.8605e-06,
+  "pairs_time": 4.76198e-07,
+  "pair_scoring_time": 5.13216e-06,
+  "grouping_time": 1.41978e-06,
+  "full_time": 6.60292e-06,
+  "merge_time": 2.97085e-06,
+  "post_time": 6.31724e-06,
+  "convert_time": 1.13797e-07,
+  "total_time": 3.53814e-05
 }
 {
   "person_nums": {
     "total_frames": 222,
     "total_labels": 376,
-    "total_preds": 442,
+    "total_preds": 454,
     "considered_empty": 0,
     "valid_preds": 376,
-    "invalid_preds": 66,
+    "invalid_preds": 78,
     "missing": 0,
-    "invalid_fraction": 0.14932,
-    "precision": 0.85068,
+    "invalid_fraction": 0.17181,
+    "precision": 0.82819,
     "recall": 1.0,
-    "f1": 0.91932,
-    "non_empty": 442
+    "f1": 0.90602,
+    "non_empty": 454
   },
   "mpjpe": {
     "count": 376,
-    "mean": 0.075547,
-    "median": 0.072512,
-    "std": 0.016669,
-    "sem": 0.000861,
+    "mean": 0.075162,
+    "median": 0.072556,
+    "std": 0.014034,
+    "sem": 0.000725,
     "min": 0.039602,
-    "max": 0.239068,
+    "max": 0.1325,
     "recall-0.025": 0.0,
     "recall-0.05": 0.00266,
-    "recall-0.1": 0.930851,
-    "recall-0.15": 0.99734,
+    "recall-0.1": 0.93883,
+    "recall-0.15": 1.0,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 376,
     "ap-0.025": 0.0,
     "ap-0.05": 4e-05,
-    "ap-0.1": 0.851885,
-    "ap-0.15": 0.965231,
-    "ap-0.25": 0.967694,
-    "ap-0.5": 0.967694
+    "ap-0.1": 0.858799,
+    "ap-0.15": 0.966406,
+    "ap-0.25": 0.966406,
+    "ap-0.5": 0.966406
   },
   "head": {
     "count": 376,
@@ -677,97 +680,97 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_left": {
     "count": 376,
-    "mean": 0.067112,
-    "median": 0.064801,
-    "std": 0.030176,
-    "sem": 0.001558,
+    "mean": 0.066762,
+    "median": 0.064778,
+    "std": 0.029588,
+    "sem": 0.001528,
     "min": 0.013559,
     "max": 0.205286,
     "recall-0.025": 0.045213,
     "recall-0.05": 0.321809,
-    "recall-0.1": 0.882979,
-    "recall-0.15": 0.981383,
+    "recall-0.1": 0.885638,
+    "recall-0.15": 0.984043,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "shoulder_right": {
     "count": 376,
-    "mean": 0.070564,
+    "mean": 0.069569,
     "median": 0.06227,
-    "std": 0.038676,
-    "sem": 0.001997,
+    "std": 0.031907,
+    "sem": 0.001648,
     "min": 0.017146,
-    "max": 0.497202,
+    "max": 0.198854,
     "recall-0.025": 0.018617,
     "recall-0.05": 0.31117,
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+    "recall-0.15": 0.970745,
+    "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "elbow_left": {
     "count": 376,
-    "mean": 0.090691,
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     "median": 0.073021,
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+    "std": 0.053197,
+    "sem": 0.002747,
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     "recall-0.05": 0.236702,
     "recall-0.1": 0.646277,
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     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "elbow_right": {
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-    "mean": 0.077657,
-    "median": 0.070602,
-    "std": 0.037828,
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+    "mean": 0.077673,
+    "median": 0.070847,
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+    "sem": 0.001951,
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     "max": 0.184804,
     "recall-0.025": 0.037234,
     "recall-0.05": 0.276596,
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-    "recall-0.15": 0.93883,
-    "recall-0.25": 0.99734,
-    "recall-0.5": 0.99734,
+    "recall-0.1": 0.726064,
+    "recall-0.15": 0.941489,
+    "recall-0.25": 1.0,
+    "recall-0.5": 1.0,
     "num_labels": 376
   },
   "wrist_left": {
     "count": 376,
-    "mean": 0.130122,
-    "median": 0.115218,
-    "std": 0.069844,
-    "sem": 0.003607,
+    "mean": 0.13004,
+    "median": 0.115432,
+    "std": 0.068219,
+    "sem": 0.003523,
     "min": 0.017061,
-    "max": 0.459038,
+    "max": 0.345868,
     "recall-0.025": 0.013298,
     "recall-0.05": 0.077128,
-    "recall-0.1": 0.398936,
-    "recall-0.15": 0.675532,
-    "recall-0.25": 0.920213,
+    "recall-0.1": 0.396277,
+    "recall-0.15": 0.672872,
+    "recall-0.25": 0.922872,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "wrist_right": {
     "count": 376,
-    "mean": 0.103967,
-    "median": 0.097173,
-    "std": 0.050063,
-    "sem": 0.002585,
+    "mean": 0.101756,
+    "median": 0.096874,
+    "std": 0.044372,
+    "sem": 0.002291,
     "min": 0.00426,
-    "max": 0.461637,
+    "max": 0.279842,
     "recall-0.025": 0.005319,
     "recall-0.05": 0.101064,
-    "recall-0.1": 0.515957,
-    "recall-0.15": 0.851064,
-    "recall-0.25": 0.986702,
+    "recall-0.1": 0.523936,
+    "recall-0.15": 0.861702,
+    "recall-0.25": 0.992021,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
@@ -821,66 +824,66 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_right": {
     "count": 376,
-    "mean": 0.054065,
+    "mean": 0.054043,
     "median": 0.049743,
-    "std": 0.027363,
-    "sem": 0.001413,
+    "std": 0.027289,
+    "sem": 0.001409,
     "min": 0.011142,
     "max": 0.228754,
     "recall-0.025": 0.077128,
     "recall-0.05": 0.505319,
     "recall-0.1": 0.952128,
-    "recall-0.15": 0.989362,
+    "recall-0.15": 0.992021,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "ankle_left": {
     "count": 376,
-    "mean": 0.070912,
-    "median": 0.064896,
-    "std": 0.044349,
-    "sem": 0.00229,
+    "mean": 0.071464,
+    "median": 0.065404,
+    "std": 0.04228,
+    "sem": 0.002183,
     "min": 0.010298,
-    "max": 0.401341,
+    "max": 0.378232,
     "recall-0.025": 0.045213,
     "recall-0.05": 0.329787,
-    "recall-0.1": 0.875,
-    "recall-0.15": 0.968085,
-    "recall-0.25": 0.986702,
+    "recall-0.1": 0.861702,
+    "recall-0.15": 0.954787,
+    "recall-0.25": 0.992021,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "ankle_right": {
     "count": 376,
-    "mean": 0.065105,
+    "mean": 0.065216,
     "median": 0.052692,
-    "std": 0.049817,
-    "sem": 0.002573,
+    "std": 0.047867,
+    "sem": 0.002472,
     "min": 0.0034,
     "max": 0.378972,
-    "recall-0.025": 0.066489,
+    "recall-0.025": 0.069149,
     "recall-0.05": 0.43617,
-    "recall-0.1": 0.880319,
-    "recall-0.15": 0.957447,
-    "recall-0.25": 0.984043,
+    "recall-0.1": 0.87234,
+    "recall-0.15": 0.952128,
+    "recall-0.25": 0.986702,
     "recall-0.5": 1.0,
     "num_labels": 376
   },
   "joint_recalls": {
     "num_labels": 4888,
-    "recall-0.025": 0.03908,
+    "recall-0.025": 0.03948,
     "recall-0.05": 0.29828,
-    "recall-0.1": 0.79971,
-    "recall-0.15": 0.93515,
-    "recall-0.25": 0.98813,
-    "recall-0.5": 0.99959
+    "recall-0.1": 0.7989,
+    "recall-0.15": 0.93453,
+    "recall-0.25": 0.99018,
+    "recall-0.5": 1.0
   }
 }
 {
   "total_parts": 5264,
-  "correct_parts": 5005,
-  "pcp": 0.950798
+  "correct_parts": 5013,
+  "pcp": 0.952318
 }
 ```
 
@@ -892,6 +895,7 @@ Results of the model in various experiments on different datasets. \
   "demosaicing": 0.0002937,
   "avg_time_2d": 0.00802104,
   "avg_time_3d": 4.47021e-05,
+  "time_tracks": 0,
   "fps": 119.625
 }
 {
@@ -1111,680 +1115,107 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0472362,
-  "demosaicing": 0.00104078,
-  "avg_time_2d": 0.016779,
-  "avg_time_3d": 0.000147258,
-  "fps": 55.6575
+  "img_loading": 0.0479199,
+  "demosaicing": 0.00102993,
+  "avg_time_2d": 0.0167737,
+  "avg_time_3d": 0.000150704,
+  "time_tracks": 1.38331e-06,
+  "fps": 55.6924
 }
 {
   "triangulator_calls": 420,
-  "init_time": 2.83825e-06,
-  "undistort_time": 1.62245e-05,
-  "project_time": 2.73635e-06,
-  "match_time": 1.22068e-05,
-  "pairs_time": 7.67092e-06,
-  "pair_scoring_time": 3.49176e-05,
-  "grouping_time": 7.59939e-06,
-  "full_time": 2.92463e-05,
-  "merge_time": 1.35496e-05,
-  "post_time": 8.52639e-06,
-  "convert_time": 1.49119e-07,
-  "total_time": 0.000135899
+  "init_time": 3.30566e-06,
+  "undistort_time": 1.61718e-05,
+  "project_time": 2.97576e-06,
+  "match_time": 1.2894e-05,
+  "pairs_time": 8.03232e-06,
+  "pair_scoring_time": 3.56451e-05,
+  "grouping_time": 7.91833e-06,
+  "full_time": 2.95268e-05,
+  "merge_time": 1.38784e-05,
+  "post_time": 8.84109e-06,
+  "convert_time": 1.9884e-07,
+  "total_time": 0.000139622
 }
 {
   "person_nums": {
     "total_frames": 420,
     "total_labels": 1466,
-    "total_preds": 1488,
+    "total_preds": 1491,
     "considered_empty": 0,
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-    "invalid_preds": 26,
-    "missing": 4,
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-    "precision": 0.98253,
-    "recall": 0.99727,
-    "f1": 0.98984,
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+    "valid_preds": 1463,
+    "invalid_preds": 28,
+    "missing": 3,
+    "invalid_fraction": 0.01878,
+    "precision": 0.98122,
+    "recall": 0.99795,
+    "f1": 0.98952,
+    "non_empty": 1491
   },
   "mpjpe": {
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     "num_labels": 1466,
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-    "ap-0.15": 0.99524,
-    "ap-0.25": 0.99524,
-    "ap-0.5": 0.99524
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+    "ap-0.15": 0.995779,
+    "ap-0.25": 0.995779,
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   },
   "nose": {
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     "recall-0.15": 0.995899,
     "recall-0.25": 0.996582,
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     "num_labels": 1463
   },
   "shoulder_left": {
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-    "num_labels": 1434
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-  "wrist_right": {
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-    "num_labels": 1456
-  },
-  "hip_left": {
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-    "mean": 0.035183,
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-    "num_labels": 1465
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-    "recall-0.25": 0.996589,
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-    "num_labels": 1466
-  },
-  "knee_left": {
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-    "mean": 0.037426,
-    "median": 0.032762,
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-    "sem": 0.000765,
-    "min": 0.00406,
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-    "recall-0.025": 0.296928,
-    "recall-0.05": 0.812969,
-    "recall-0.1": 0.979522,
-    "recall-0.15": 0.989078,
-    "recall-0.25": 0.993174,
-    "recall-0.5": 0.99727,
-    "num_labels": 1465
-  },
-  "knee_right": {
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-    "mean": 0.03731,
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-    "std": 0.025418,
-    "sem": 0.000667,
-    "min": 0.004194,
-    "max": 0.363111,
-    "recall-0.025": 0.371487,
-    "recall-0.05": 0.76902,
-    "recall-0.1": 0.969842,
-    "recall-0.15": 0.994517,
-    "recall-0.25": 0.996573,
-    "recall-0.5": 0.997258,
-    "num_labels": 1459
-  },
-  "ankle_left": {
-    "count": 1459,
-    "mean": 0.050406,
-    "median": 0.031859,
-    "std": 0.054672,
-    "sem": 0.001432,
-    "min": 0.003265,
-    "max": 0.439571,
-    "recall-0.025": 0.370472,
-    "recall-0.05": 0.700615,
-    "recall-0.1": 0.882433,
-    "recall-0.15": 0.944634,
-    "recall-0.25": 0.980861,
-    "recall-0.5": 0.997266,
-    "num_labels": 1463
-  },
-  "ankle_right": {
-    "count": 1452,
-    "mean": 0.048536,
-    "median": 0.031361,
-    "std": 0.058339,
-    "sem": 0.001532,
-    "min": 0.002507,
-    "max": 0.485436,
-    "recall-0.025": 0.367808,
-    "recall-0.05": 0.757534,
-    "recall-0.1": 0.895205,
-    "recall-0.15": 0.926712,
-    "recall-0.25": 0.974658,
-    "recall-0.5": 0.994521,
-    "num_labels": 1460
-  },
-  "joint_recalls": {
-    "num_labels": 18990,
-    "recall-0.025": 0.58668,
-    "recall-0.05": 0.86493,
-    "recall-0.1": 0.96551,
-    "recall-0.15": 0.98194,
-    "recall-0.25": 0.99236,
-    "recall-0.5": 0.99726
-  }
-}
-{
-  "total_parts": 20444,
-  "correct_parts": 20243,
-  "pcp": 0.990168
-}
-```
-
-##### 3 cameras
-
-```json
-{
-  "img_loading": 0.0292945,
-  "demosaicing": 0.000700228,
-  "avg_time_2d": 0.0100312,
-  "avg_time_3d": 6.66628e-05,
-  "fps": 92.6094
-}
-{
-  "triangulator_calls": 420,
-  "init_time": 2.95553e-06,
-  "undistort_time": 9.92935e-06,
-  "project_time": 1.49162e-06,
-  "match_time": 7.1829e-06,
-  "pairs_time": 2.24381e-06,
-  "pair_scoring_time": 1.12116e-05,
-  "grouping_time": 2.81234e-06,
-  "full_time": 1.00224e-05,
-  "merge_time": 5.28941e-06,
-  "post_time": 7.89963e-06,
-  "convert_time": 1.68905e-07,
-  "total_time": 6.14426e-05
-}
-{
-  "person_nums": {
-    "total_frames": 420,
-    "total_labels": 1466,
-    "total_preds": 1379,
-    "considered_empty": 0,
-    "valid_preds": 1366,
-    "invalid_preds": 13,
-    "missing": 100,
-    "invalid_fraction": 0.00943,
-    "precision": 0.99057,
-    "recall": 0.93179,
-    "f1": 0.96028,
-    "non_empty": 1379
-  },
-  "mpjpe": {
-    "count": 1366,
-    "mean": 0.056595,
-    "median": 0.045554,
-    "std": 0.03804,
-    "sem": 0.00103,
-    "min": 0.018518,
-    "max": 0.348157,
-    "recall-0.025": 0.018417,
-    "recall-0.05": 0.547067,
-    "recall-0.1": 0.84925,
-    "recall-0.15": 0.902456,
-    "recall-0.25": 0.925648,
-    "recall-0.5": 0.931787,
-    "num_labels": 1466,
-    "ap-0.025": 0.004947,
-    "ap-0.05": 0.4475,
-    "ap-0.1": 0.826634,
-    "ap-0.15": 0.892219,
-    "ap-0.25": 0.917603,
-    "ap-0.5": 0.924455
-  },
-  "nose": {
-    "count": 1365,
-    "mean": 0.023824,
-    "median": 0.018351,
-    "std": 0.017653,
-    "sem": 0.000478,
-    "min": 0.00138,
-    "max": 0.130817,
-    "recall-0.025": 0.611073,
-    "recall-0.05": 0.848257,
-    "recall-0.1": 0.926863,
-    "recall-0.15": 0.933014,
-    "recall-0.25": 0.933014,
-    "recall-0.5": 0.933014,
-    "num_labels": 1463
-  },
-  "shoulder_left": {
-    "count": 1366,
-    "mean": 0.020138,
-    "median": 0.016525,
-    "std": 0.014325,
-    "sem": 0.000388,
-    "min": 0.000838,
-    "max": 0.118475,
-    "recall-0.025": 0.701228,
-    "recall-0.05": 0.901774,
-    "recall-0.1": 0.927694,
-    "recall-0.15": 0.931787,
-    "recall-0.25": 0.931787,
-    "recall-0.5": 0.931787,
-    "num_labels": 1466
-  },
-  "shoulder_right": {
-    "count": 1365,
-    "mean": 0.022731,
-    "median": 0.017688,
-    "std": 0.018447,
-    "sem": 0.000499,
-    "min": 0.002084,
-    "max": 0.215048,
-    "recall-0.025": 0.653242,
-    "recall-0.05": 0.87372,
-    "recall-0.1": 0.926962,
-    "recall-0.15": 0.928328,
-    "recall-0.25": 0.931741,
-    "recall-0.5": 0.931741,
-    "num_labels": 1465
-  },
-  "elbow_left": {
-    "count": 1365,
-    "mean": 0.032839,
-    "median": 0.021354,
-    "std": 0.031501,
-    "sem": 0.000853,
-    "min": 0.00105,
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-    "recall-0.025": 0.546758,
-    "recall-0.05": 0.757679,
-    "recall-0.1": 0.877133,
-    "recall-0.15": 0.926962,
-    "recall-0.25": 0.929693,
-    "recall-0.5": 0.931741,
-    "num_labels": 1465
-  },
-  "elbow_right": {
-    "count": 1365,
-    "mean": 0.031128,
-    "median": 0.021108,
-    "std": 0.031112,
-    "sem": 0.000842,
-    "min": 0.002016,
-    "max": 0.325627,
-    "recall-0.025": 0.57553,
-    "recall-0.05": 0.788107,
-    "recall-0.1": 0.901572,
-    "recall-0.15": 0.924129,
-    "recall-0.25": 0.930964,
-    "recall-0.5": 0.933014,
-    "num_labels": 1463
-  },
-  "wrist_left": {
-    "count": 1336,
-    "mean": 0.052095,
-    "median": 0.02347,
-    "std": 0.063364,
-    "sem": 0.001734,
-    "min": 0.001228,
-    "max": 0.492913,
-    "recall-0.025": 0.486053,
-    "recall-0.05": 0.651325,
-    "recall-0.1": 0.778243,
-    "recall-0.15": 0.837517,
-    "recall-0.25": 0.91841,
-    "recall-0.5": 0.93166,
-    "num_labels": 1434
-  },
-  "wrist_right": {
-    "count": 1359,
-    "mean": 0.047294,
-    "median": 0.024005,
-    "std": 0.059423,
-    "sem": 0.001613,
-    "min": 0.001712,
-    "max": 0.353775,
-    "recall-0.025": 0.486951,
-    "recall-0.05": 0.679945,
-    "recall-0.1": 0.820742,
-    "recall-0.15": 0.873626,
-    "recall-0.25": 0.907967,
-    "recall-0.5": 0.933379,
-    "num_labels": 1456
-  },
-  "hip_left": {
-    "count": 1365,
-    "mean": 0.042968,
-    "median": 0.037811,
-    "std": 0.026631,
-    "sem": 0.000721,
-    "min": 0.001201,
-    "max": 0.370723,
-    "recall-0.025": 0.201365,
-    "recall-0.05": 0.666894,
-    "recall-0.1": 0.908532,
-    "recall-0.15": 0.927645,
-    "recall-0.25": 0.930375,
-    "recall-0.5": 0.931741,
-    "num_labels": 1465
-  },
-  "hip_right": {
-    "count": 1366,
-    "mean": 0.05136,
-    "median": 0.043963,
-    "std": 0.032543,
-    "sem": 0.000881,
-    "min": 0.004905,
-    "max": 0.27157,
-    "recall-0.025": 0.154161,
-    "recall-0.05": 0.542974,
-    "recall-0.1": 0.873806,
-    "recall-0.15": 0.918145,
-    "recall-0.25": 0.929741,
-    "recall-0.5": 0.931787,
-    "num_labels": 1466
-  },
-  "knee_left": {
-    "count": 1353,
-    "mean": 0.057829,
-    "median": 0.04077,
-    "std": 0.064952,
-    "sem": 0.001766,
-    "min": 0.003716,
-    "max": 0.396038,
-    "recall-0.025": 0.217065,
-    "recall-0.05": 0.590444,
-    "recall-0.1": 0.837543,
-    "recall-0.15": 0.868259,
-    "recall-0.25": 0.895563,
-    "recall-0.5": 0.923549,
-    "num_labels": 1465
-  },
-  "knee_right": {
-    "count": 1350,
-    "mean": 0.063263,
-    "median": 0.045916,
-    "std": 0.063862,
-    "sem": 0.001739,
-    "min": 0.006358,
-    "max": 0.413608,
-    "recall-0.025": 0.141193,
-    "recall-0.05": 0.514736,
-    "recall-0.1": 0.833448,
-    "recall-0.15": 0.860178,
-    "recall-0.25": 0.893763,
-    "recall-0.5": 0.925291,
-    "num_labels": 1459
-  },
-  "ankle_left": {
-    "count": 1298,
-    "mean": 0.108053,
-    "median": 0.070214,
-    "std": 0.110487,
-    "sem": 0.003068,
-    "min": 0.002475,
-    "max": 0.497978,
-    "recall-0.025": 0.168148,
-    "recall-0.05": 0.367738,
-    "recall-0.1": 0.576213,
-    "recall-0.15": 0.682843,
-    "recall-0.25": 0.768968,
-    "recall-0.5": 0.887218,
-    "num_labels": 1463
-  },
-  "ankle_right": {
-    "count": 1283,
-    "mean": 0.108268,
-    "median": 0.051324,
-    "std": 0.117911,
-    "sem": 0.003293,
-    "min": 0.002089,
-    "max": 0.499606,
-    "recall-0.025": 0.173288,
-    "recall-0.05": 0.426027,
-    "recall-0.1": 0.585616,
-    "recall-0.15": 0.641781,
-    "recall-0.25": 0.743151,
-    "recall-0.5": 0.878767,
-    "num_labels": 1460
-  },
-  "joint_recalls": {
-    "num_labels": 18990,
-    "recall-0.025": 0.39331,
-    "recall-0.05": 0.66198,
-    "recall-0.1": 0.82854,
-    "recall-0.15": 0.86535,
-    "recall-0.25": 0.89547,
-    "recall-0.5": 0.92296
-  }
-}
-{
-  "total_parts": 20444,
-  "correct_parts": 18282,
-  "pcp": 0.894248
-}
-```
-
-##### 7 cameras
-
-```json
-{
-  "img_loading": 0.0691732,
-  "demosaicing": 0.00157471,
-  "avg_time_2d": 0.0235997,
-  "avg_time_3d": 0.000278223,
-  "fps": 39.2887
-}
-{
-  "triangulator_calls": 420,
-  "init_time": 4.45287e-06,
-  "undistort_time": 2.29917e-05,
-  "project_time": 4.28683e-06,
-  "match_time": 1.83516e-05,
-  "pairs_time": 1.81177e-05,
-  "pair_scoring_time": 7.50915e-05,
-  "grouping_time": 1.66607e-05,
-  "full_time": 6.10801e-05,
-  "merge_time": 2.87935e-05,
-  "post_time": 9.30181e-06,
-  "convert_time": 1.58762e-07,
-  "total_time": 0.000259525
-}
-{
-  "person_nums": {
-    "total_frames": 420,
-    "total_labels": 1466,
-    "total_preds": 1516,
-    "considered_empty": 0,
-    "valid_preds": 1463,
-    "invalid_preds": 53,
-    "missing": 3,
-    "invalid_fraction": 0.03496,
-    "precision": 0.96504,
-    "recall": 0.99795,
-    "f1": 0.98122,
-    "non_empty": 1516
-  },
-  "mpjpe": {
-    "count": 1463,
-    "mean": 0.02777,
-    "median": 0.024836,
-    "std": 0.010928,
-    "sem": 0.000286,
-    "min": 0.010042,
-    "max": 0.100122,
-    "recall-0.025": 0.508186,
-    "recall-0.05": 0.952933,
     "recall-0.1": 0.997271,
     "recall-0.15": 0.997954,
     "recall-0.25": 0.997954,
     "recall-0.5": 0.997954,
-    "num_labels": 1466,
-    "ap-0.025": 0.363178,
-    "ap-0.05": 0.931973,
-    "ap-0.1": 0.988724,
-    "ap-0.15": 0.990273,
-    "ap-0.25": 0.990273,
-    "ap-0.5": 0.990273
-  },
-  "nose": {
-    "count": 1460,
-    "mean": 0.013217,
-    "median": 0.010495,
-    "std": 0.014266,
-    "sem": 0.000373,
-    "min": 0.002442,
-    "max": 0.276078,
-    "recall-0.025": 0.931647,
-    "recall-0.05": 0.984279,
-    "recall-0.1": 0.995899,
-    "recall-0.15": 0.995899,
-    "recall-0.25": 0.995899,
-    "recall-0.5": 0.997949,
-    "num_labels": 1463
-  },
-  "shoulder_left": {
-    "count": 1463,
-    "mean": 0.014306,
-    "median": 0.01258,
-    "std": 0.008789,
-    "sem": 0.00023,
-    "min": 0.000678,
-    "max": 0.066125,
-    "recall-0.025": 0.889495,
-    "recall-0.05": 0.991132,
-    "recall-0.1": 0.997954,
-    "recall-0.15": 0.997954,
-    "recall-0.25": 0.997954,
-    "recall-0.5": 0.997954,
     "num_labels": 1466
   },
   "shoulder_right": {
     "count": 1462,
-    "mean": 0.015837,
-    "median": 0.013118,
-    "std": 0.010557,
-    "sem": 0.000276,
-    "min": 0.000866,
-    "max": 0.108435,
-    "recall-0.025": 0.845734,
-    "recall-0.05": 0.983618,
+    "mean": 0.016612,
+    "median": 0.014272,
+    "std": 0.011142,
+    "sem": 0.000292,
+    "min": 0.001248,
+    "max": 0.147753,
+    "recall-0.025": 0.833447,
+    "recall-0.05": 0.986348,
     "recall-0.1": 0.99727,
     "recall-0.15": 0.997952,
     "recall-0.25": 0.997952,
@@ -1793,178 +1224,754 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_left": {
     "count": 1462,
-    "mean": 0.018735,
-    "median": 0.015662,
-    "std": 0.013059,
-    "sem": 0.000342,
-    "min": 0.000432,
-    "max": 0.142625,
-    "recall-0.025": 0.799317,
-    "recall-0.05": 0.96587,
-    "recall-0.1": 0.996587,
-    "recall-0.15": 0.997952,
-    "recall-0.25": 0.997952,
+    "mean": 0.022011,
+    "median": 0.015913,
+    "std": 0.02096,
+    "sem": 0.000548,
+    "min": 0.00084,
+    "max": 0.281775,
+    "recall-0.025": 0.752901,
+    "recall-0.05": 0.916041,
+    "recall-0.1": 0.990444,
+    "recall-0.15": 0.995222,
+    "recall-0.25": 0.996587,
     "recall-0.5": 0.997952,
     "num_labels": 1465
   },
   "elbow_right": {
-    "count": 1460,
-    "mean": 0.018781,
-    "median": 0.015557,
-    "std": 0.013965,
-    "sem": 0.000366,
-    "min": 0.001389,
-    "max": 0.15785,
-    "recall-0.025": 0.840055,
-    "recall-0.05": 0.958305,
-    "recall-0.1": 0.993848,
-    "recall-0.15": 0.997266,
-    "recall-0.25": 0.997949,
-    "recall-0.5": 0.997949,
+    "count": 1462,
+    "mean": 0.020344,
+    "median": 0.015717,
+    "std": 0.015692,
+    "sem": 0.000411,
+    "min": 0.001752,
+    "max": 0.161231,
+    "recall-0.025": 0.801777,
+    "recall-0.05": 0.945318,
+    "recall-0.1": 0.997266,
+    "recall-0.15": 0.998633,
+    "recall-0.25": 0.999316,
+    "recall-0.5": 0.999316,
     "num_labels": 1463
   },
   "wrist_left": {
-    "count": 1431,
-    "mean": 0.023223,
-    "median": 0.01503,
-    "std": 0.026136,
-    "sem": 0.000691,
-    "min": 0.000898,
-    "max": 0.222116,
-    "recall-0.025": 0.737099,
-    "recall-0.05": 0.911437,
-    "recall-0.1": 0.967922,
-    "recall-0.15": 0.987448,
-    "recall-0.25": 0.997908,
-    "recall-0.5": 0.997908,
+    "count": 1432,
+    "mean": 0.03242,
+    "median": 0.015947,
+    "std": 0.048128,
+    "sem": 0.001272,
+    "min": 0.00015,
+    "max": 0.400667,
+    "recall-0.025": 0.698047,
+    "recall-0.05": 0.856346,
+    "recall-0.1": 0.927476,
+    "recall-0.15": 0.962343,
+    "recall-0.25": 0.982566,
+    "recall-0.5": 0.998605,
     "num_labels": 1434
   },
   "wrist_right": {
-    "count": 1455,
-    "mean": 0.022685,
-    "median": 0.01411,
-    "std": 0.029711,
-    "sem": 0.000779,
-    "min": 0.001174,
-    "max": 0.311362,
-    "recall-0.025": 0.76511,
-    "recall-0.05": 0.923764,
-    "recall-0.1": 0.973901,
+    "count": 1456,
+    "mean": 0.025538,
+    "median": 0.016124,
+    "std": 0.031791,
+    "sem": 0.000833,
+    "min": 0.001381,
+    "max": 0.279434,
+    "recall-0.025": 0.703297,
+    "recall-0.05": 0.904533,
+    "recall-0.1": 0.971154,
     "recall-0.15": 0.98489,
-    "recall-0.25": 0.996566,
-    "recall-0.5": 0.999313,
+    "recall-0.25": 0.998626,
+    "recall-0.5": 1.0,
     "num_labels": 1456
   },
   "hip_left": {
     "count": 1462,
-    "mean": 0.029493,
-    "median": 0.027594,
-    "std": 0.015436,
-    "sem": 0.000404,
-    "min": 0.001996,
-    "max": 0.12705,
-    "recall-0.025": 0.436177,
-    "recall-0.05": 0.897611,
-    "recall-0.1": 0.995904,
-    "recall-0.15": 0.997952,
+    "mean": 0.035237,
+    "median": 0.030458,
+    "std": 0.023117,
+    "sem": 0.000605,
+    "min": 0.002484,
+    "max": 0.231182,
+    "recall-0.025": 0.346075,
+    "recall-0.05": 0.842321,
+    "recall-0.1": 0.980887,
+    "recall-0.15": 0.992491,
     "recall-0.25": 0.997952,
     "recall-0.5": 0.997952,
     "num_labels": 1465
   },
   "hip_right": {
     "count": 1463,
-    "mean": 0.032338,
-    "median": 0.028867,
-    "std": 0.01861,
-    "sem": 0.000487,
-    "min": 0.001585,
-    "max": 0.196952,
-    "recall-0.025": 0.389495,
-    "recall-0.05": 0.866985,
-    "recall-0.1": 0.991814,
+    "mean": 0.036829,
+    "median": 0.032162,
+    "std": 0.024043,
+    "sem": 0.000629,
+    "min": 0.003239,
+    "max": 0.27157,
+    "recall-0.025": 0.33015,
+    "recall-0.05": 0.804911,
+    "recall-0.1": 0.978172,
     "recall-0.15": 0.994543,
-    "recall-0.25": 0.997954,
+    "recall-0.25": 0.997271,
     "recall-0.5": 0.997954,
     "num_labels": 1466
   },
   "knee_left": {
     "count": 1462,
-    "mean": 0.031934,
-    "median": 0.028307,
-    "std": 0.018752,
-    "sem": 0.000491,
-    "min": 0.002743,
-    "max": 0.153637,
-    "recall-0.025": 0.416382,
-    "recall-0.05": 0.864846,
-    "recall-0.1": 0.989078,
-    "recall-0.15": 0.996587,
-    "recall-0.25": 0.997952,
+    "mean": 0.037451,
+    "median": 0.032777,
+    "std": 0.029225,
+    "sem": 0.000765,
+    "min": 0.00406,
+    "max": 0.464241,
+    "recall-0.025": 0.296928,
+    "recall-0.05": 0.812969,
+    "recall-0.1": 0.980205,
+    "recall-0.15": 0.989761,
+    "recall-0.25": 0.993857,
     "recall-0.5": 0.997952,
     "num_labels": 1465
   },
   "knee_right": {
-    "count": 1457,
-    "mean": 0.034476,
-    "median": 0.03083,
-    "std": 0.019836,
+    "count": 1456,
+    "mean": 0.037347,
+    "median": 0.031036,
+    "std": 0.02543,
+    "sem": 0.000667,
+    "min": 0.004194,
+    "max": 0.363111,
+    "recall-0.025": 0.371487,
+    "recall-0.05": 0.768334,
+    "recall-0.1": 0.970528,
+    "recall-0.15": 0.995202,
+    "recall-0.25": 0.997258,
+    "recall-0.5": 0.997944,
+    "num_labels": 1459
+  },
+  "ankle_left": {
+    "count": 1460,
+    "mean": 0.050611,
+    "median": 0.032049,
+    "std": 0.054472,
+    "sem": 0.001426,
+    "min": 0.003265,
+    "max": 0.439571,
+    "recall-0.025": 0.370472,
+    "recall-0.05": 0.697881,
+    "recall-0.1": 0.879699,
+    "recall-0.15": 0.945318,
+    "recall-0.25": 0.982228,
+    "recall-0.5": 0.997949,
+    "num_labels": 1463
+  },
+  "ankle_right": {
+    "count": 1453,
+    "mean": 0.048936,
+    "median": 0.031418,
+    "std": 0.058915,
+    "sem": 0.001546,
+    "min": 0.002507,
+    "max": 0.485436,
+    "recall-0.025": 0.367123,
+    "recall-0.05": 0.755479,
+    "recall-0.1": 0.894521,
+    "recall-0.15": 0.926027,
+    "recall-0.25": 0.974658,
+    "recall-0.5": 0.995205,
+    "num_labels": 1460
+  },
+  "joint_recalls": {
+    "num_labels": 18990,
+    "recall-0.025": 0.58662,
+    "recall-0.05": 0.86445,
+    "recall-0.1": 0.96593,
+    "recall-0.15": 0.98246,
+    "recall-0.25": 0.99279,
+    "recall-0.5": 0.99768
+  }
+}
+{
+  "total_parts": 20444,
+  "correct_parts": 20255,
+  "pcp": 0.990755
+}
+```
+
+##### 3 cameras
+
+```json
+{
+  "img_loading": 0.0297065,
+  "demosaicing": 0.000688111,
+  "avg_time_2d": 0.0099169,
+  "avg_time_3d": 6.60544e-05,
+  "time_tracks": 1.16308e-06,
+  "fps": 93.7012
+}
+{
+  "triangulator_calls": 420,
+  "init_time": 2.94144e-06,
+  "undistort_time": 9.86922e-06,
+  "project_time": 1.48401e-06,
+  "match_time": 7.04053e-06,
+  "pairs_time": 2.2787e-06,
+  "pair_scoring_time": 1.10473e-05,
+  "grouping_time": 2.84531e-06,
+  "full_time": 9.9795e-06,
+  "merge_time": 5.23312e-06,
+  "post_time": 7.87855e-06,
+  "convert_time": 1.79293e-07,
+  "total_time": 6.10098e-05
+}
+{
+  "person_nums": {
+    "total_frames": 420,
+    "total_labels": 1466,
+    "total_preds": 1405,
+    "considered_empty": 0,
+    "valid_preds": 1387,
+    "invalid_preds": 18,
+    "missing": 79,
+    "invalid_fraction": 0.01281,
+    "precision": 0.98719,
+    "recall": 0.94611,
+    "f1": 0.96621,
+    "non_empty": 1405
+  },
+  "mpjpe": {
+    "count": 1387,
+    "mean": 0.057809,
+    "median": 0.045733,
+    "std": 0.039393,
+    "sem": 0.001058,
+    "min": 0.018518,
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+    "recall-0.15": 0.912005,
+    "recall-0.25": 0.939973,
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+    "num_labels": 1466,
+    "ap-0.025": 0.004084,
+    "ap-0.05": 0.446064,
+    "ap-0.1": 0.826788,
+    "ap-0.15": 0.900299,
+    "ap-0.25": 0.930765,
+    "ap-0.5": 0.937125
+  },
+  "nose": {
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+    "mean": 0.024278,
+    "median": 0.0185,
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+    "sem": 0.000503,
+    "min": 0.00138,
+    "max": 0.185287,
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+    "recall-0.05": 0.857143,
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+    "recall-0.15": 0.946685,
+    "recall-0.25": 0.947368,
+    "recall-0.5": 0.947368,
+    "num_labels": 1463
+  },
+  "shoulder_left": {
+    "count": 1387,
+    "mean": 0.020631,
+    "median": 0.016653,
+    "std": 0.016094,
+    "sem": 0.000432,
+    "min": 0.000838,
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+    "recall-0.025": 0.706003,
+    "recall-0.05": 0.911323,
+    "recall-0.1": 0.939973,
+    "recall-0.15": 0.944748,
+    "recall-0.25": 0.946112,
+    "recall-0.5": 0.946112,
+    "num_labels": 1466
+  },
+  "shoulder_right": {
+    "count": 1386,
+    "mean": 0.023485,
+    "median": 0.017809,
+    "std": 0.021117,
+    "sem": 0.000567,
+    "min": 0.002084,
+    "max": 0.215048,
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+    "recall-0.05": 0.883276,
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+    "recall-0.15": 0.939932,
+    "recall-0.25": 0.946075,
+    "recall-0.5": 0.946075,
+    "num_labels": 1465
+  },
+  "elbow_left": {
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+    "mean": 0.033508,
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+    "recall-0.15": 0.939932,
+    "recall-0.25": 0.942662,
+    "recall-0.5": 0.946075,
+    "num_labels": 1465
+  },
+  "elbow_right": {
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+    "mean": 0.031599,
+    "median": 0.021155,
+    "std": 0.032062,
+    "sem": 0.000862,
+    "min": 0.002016,
+    "max": 0.325627,
+    "recall-0.025": 0.579631,
+    "recall-0.05": 0.797676,
+    "recall-0.1": 0.912509,
+    "recall-0.15": 0.936432,
+    "recall-0.25": 0.945318,
+    "recall-0.5": 0.947368,
+    "num_labels": 1463
+  },
+  "wrist_left": {
+    "count": 1357,
+    "mean": 0.052803,
+    "median": 0.024023,
+    "std": 0.064029,
+    "sem": 0.001739,
+    "min": 0.001228,
+    "max": 0.492913,
+    "recall-0.025": 0.488145,
+    "recall-0.05": 0.656904,
+    "recall-0.1": 0.788006,
+    "recall-0.15": 0.848675,
+    "recall-0.25": 0.933054,
+    "recall-0.5": 0.946304,
+    "num_labels": 1434
+  },
+  "wrist_right": {
+    "count": 1380,
+    "mean": 0.048042,
+    "median": 0.024233,
+    "std": 0.060625,
+    "sem": 0.001633,
+    "min": 0.001712,
+    "max": 0.405436,
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+    "recall-0.15": 0.885302,
+    "recall-0.25": 0.921016,
+    "recall-0.5": 0.947802,
+    "num_labels": 1456
+  },
+  "hip_left": {
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+    "mean": 0.043694,
+    "median": 0.038134,
+    "std": 0.027801,
+    "sem": 0.000747,
+    "min": 0.001201,
+    "max": 0.370723,
+    "recall-0.025": 0.20273,
+    "recall-0.05": 0.67099,
+    "recall-0.1": 0.916724,
+    "recall-0.15": 0.940614,
+    "recall-0.25": 0.94471,
+    "recall-0.5": 0.946075,
+    "num_labels": 1465
+  },
+  "hip_right": {
+    "count": 1387,
+    "mean": 0.052384,
+    "median": 0.044002,
+    "std": 0.034873,
+    "sem": 0.000937,
+    "min": 0.004905,
+    "max": 0.27157,
+    "recall-0.025": 0.156889,
+    "recall-0.05": 0.547749,
+    "recall-0.1": 0.880628,
+    "recall-0.15": 0.92633,
+    "recall-0.25": 0.944065,
+    "recall-0.5": 0.946112,
+    "num_labels": 1466
+  },
+  "knee_left": {
+    "count": 1372,
+    "mean": 0.059338,
+    "median": 0.041103,
+    "std": 0.066615,
+    "sem": 0.001799,
+    "min": 0.003716,
+    "max": 0.396038,
+    "recall-0.025": 0.217065,
+    "recall-0.05": 0.592491,
+    "recall-0.1": 0.840273,
+    "recall-0.15": 0.873038,
+    "recall-0.25": 0.907167,
+    "recall-0.5": 0.936519,
+    "num_labels": 1465
+  },
+  "knee_right": {
+    "count": 1372,
+    "mean": 0.064953,
+    "median": 0.046186,
+    "std": 0.065917,
+    "sem": 0.00178,
+    "min": 0.006358,
+    "max": 0.413608,
+    "recall-0.025": 0.141193,
+    "recall-0.05": 0.517478,
+    "recall-0.1": 0.836875,
+    "recall-0.15": 0.866347,
+    "recall-0.25": 0.9061,
+    "recall-0.5": 0.94037,
+    "num_labels": 1459
+  },
+  "ankle_left": {
+    "count": 1313,
+    "mean": 0.109506,
+    "median": 0.071209,
+    "std": 0.111954,
+    "sem": 0.003091,
+    "min": 0.002475,
+    "max": 0.497978,
+    "recall-0.025": 0.168831,
+    "recall-0.05": 0.368421,
+    "recall-0.1": 0.578947,
+    "recall-0.15": 0.686945,
+    "recall-0.25": 0.77512,
+    "recall-0.5": 0.897471,
+    "num_labels": 1463
+  },
+  "ankle_right": {
+    "count": 1303,
+    "mean": 0.111553,
+    "median": 0.052471,
+    "std": 0.120445,
+    "sem": 0.003338,
+    "min": 0.002089,
+    "max": 0.499606,
+    "recall-0.025": 0.173288,
+    "recall-0.05": 0.425342,
+    "recall-0.1": 0.585616,
+    "recall-0.15": 0.642466,
+    "recall-0.25": 0.74589,
+    "recall-0.5": 0.892466,
+    "num_labels": 1460
+  },
+  "joint_recalls": {
+    "num_labels": 18990,
+    "recall-0.025": 0.39563,
+    "recall-0.05": 0.66751,
+    "recall-0.1": 0.83665,
+    "recall-0.15": 0.87509,
+    "recall-0.25": 0.90758,
+    "recall-0.5": 0.93697
+  }
+}
+{
+  "total_parts": 20444,
+  "correct_parts": 18490,
+  "pcp": 0.904422
+}
+```
+
+##### 7 cameras
+
+```json
+{
+  "img_loading": 0.0676695,
+  "demosaicing": 0.00167722,
+  "avg_time_2d": 0.0236274,
+  "avg_time_3d": 0.000277402,
+  "time_tracks": 1.6014e-06,
+  "fps": 39.0875
+}
+{
+  "triangulator_calls": 420,
+  "init_time": 4.12762e-06,
+  "undistort_time": 2.27581e-05,
+  "project_time": 4.2093e-06,
+  "match_time": 1.80837e-05,
+  "pairs_time": 1.92128e-05,
+  "pair_scoring_time": 7.41403e-05,
+  "grouping_time": 1.65973e-05,
+  "full_time": 6.08105e-05,
+  "merge_time": 2.83742e-05,
+  "post_time": 9.35338e-06,
+  "convert_time": 1.858e-07,
+  "total_time": 0.000258086
+}
+{
+  "person_nums": {
+    "total_frames": 420,
+    "total_labels": 1466,
+    "total_preds": 1525,
+    "considered_empty": 0,
+    "valid_preds": 1465,
+    "invalid_preds": 60,
+    "missing": 1,
+    "invalid_fraction": 0.03934,
+    "precision": 0.96066,
+    "recall": 0.99932,
+    "f1": 0.97961,
+    "non_empty": 1525
+  },
+  "mpjpe": {
+    "count": 1465,
+    "mean": 0.027872,
+    "median": 0.024928,
+    "std": 0.011052,
+    "sem": 0.000289,
+    "min": 0.010042,
+    "max": 0.11011,
+    "recall-0.025": 0.505457,
+    "recall-0.05": 0.952933,
+    "recall-0.1": 0.998636,
+    "recall-0.15": 0.999318,
+    "recall-0.25": 0.999318,
+    "recall-0.5": 0.999318,
+    "num_labels": 1466,
+    "ap-0.025": 0.360471,
+    "ap-0.05": 0.930742,
+    "ap-0.1": 0.989824,
+    "ap-0.15": 0.99048,
+    "ap-0.25": 0.99048,
+    "ap-0.5": 0.99048
+  },
+  "nose": {
+    "count": 1462,
+    "mean": 0.013451,
+    "median": 0.010507,
+    "std": 0.016174,
+    "sem": 0.000423,
+    "min": 0.002442,
+    "max": 0.300311,
+    "recall-0.025": 0.931647,
+    "recall-0.05": 0.984279,
+    "recall-0.1": 0.996582,
+    "recall-0.15": 0.996582,
+    "recall-0.25": 0.996582,
+    "recall-0.5": 0.999316,
+    "num_labels": 1463
+  },
+  "shoulder_left": {
+    "count": 1465,
+    "mean": 0.014367,
+    "median": 0.012587,
+    "std": 0.009017,
+    "sem": 0.000236,
+    "min": 0.000678,
+    "max": 0.091593,
+    "recall-0.025": 0.889495,
+    "recall-0.05": 0.991814,
+    "recall-0.1": 0.999318,
+    "recall-0.15": 0.999318,
+    "recall-0.25": 0.999318,
+    "recall-0.5": 0.999318,
+    "num_labels": 1466
+  },
+  "shoulder_right": {
+    "count": 1464,
+    "mean": 0.015886,
+    "median": 0.013121,
+    "std": 0.010646,
+    "sem": 0.000278,
+    "min": 0.000866,
+    "max": 0.108435,
+    "recall-0.025": 0.845734,
+    "recall-0.05": 0.9843,
+    "recall-0.1": 0.998635,
+    "recall-0.15": 0.999317,
+    "recall-0.25": 0.999317,
+    "recall-0.5": 0.999317,
+    "num_labels": 1465
+  },
+  "elbow_left": {
+    "count": 1464,
+    "mean": 0.0188,
+    "median": 0.015688,
+    "std": 0.013281,
+    "sem": 0.000347,
+    "min": 0.000432,
+    "max": 0.142625,
+    "recall-0.025": 0.8,
+    "recall-0.05": 0.966553,
+    "recall-0.1": 0.99727,
+    "recall-0.15": 0.999317,
+    "recall-0.25": 0.999317,
+    "recall-0.5": 0.999317,
+    "num_labels": 1465
+  },
+  "elbow_right": {
+    "count": 1462,
+    "mean": 0.018846,
+    "median": 0.015574,
+    "std": 0.014075,
+    "sem": 0.000368,
+    "min": 0.001389,
+    "max": 0.15785,
+    "recall-0.025": 0.840055,
+    "recall-0.05": 0.958305,
+    "recall-0.1": 0.995215,
+    "recall-0.15": 0.998633,
+    "recall-0.25": 0.999316,
+    "recall-0.5": 0.999316,
+    "num_labels": 1463
+  },
+  "wrist_left": {
+    "count": 1433,
+    "mean": 0.02331,
+    "median": 0.015059,
+    "std": 0.026221,
+    "sem": 0.000693,
+    "min": 0.000898,
+    "max": 0.222116,
+    "recall-0.025": 0.737099,
+    "recall-0.05": 0.911437,
+    "recall-0.1": 0.969317,
+    "recall-0.15": 0.988842,
+    "recall-0.25": 0.999303,
+    "recall-0.5": 0.999303,
+    "num_labels": 1434
+  },
+  "wrist_right": {
+    "count": 1456,
+    "mean": 0.022755,
+    "median": 0.014112,
+    "std": 0.029818,
+    "sem": 0.000782,
+    "min": 0.001174,
+    "max": 0.311362,
+    "recall-0.025": 0.76511,
+    "recall-0.05": 0.923764,
+    "recall-0.1": 0.973901,
+    "recall-0.15": 0.985577,
+    "recall-0.25": 0.997253,
+    "recall-0.5": 1.0,
+    "num_labels": 1456
+  },
+  "hip_left": {
+    "count": 1464,
+    "mean": 0.029562,
+    "median": 0.027611,
+    "std": 0.01559,
+    "sem": 0.000408,
+    "min": 0.001996,
+    "max": 0.12705,
+    "recall-0.025": 0.436177,
+    "recall-0.05": 0.898294,
+    "recall-0.1": 0.996587,
+    "recall-0.15": 0.999317,
+    "recall-0.25": 0.999317,
+    "recall-0.5": 0.999317,
+    "num_labels": 1465
+  },
+  "hip_right": {
+    "count": 1465,
+    "mean": 0.032376,
+    "median": 0.028909,
+    "std": 0.018656,
+    "sem": 0.000488,
+    "min": 0.001585,
+    "max": 0.196952,
+    "recall-0.025": 0.389495,
+    "recall-0.05": 0.867667,
+    "recall-0.1": 0.993179,
+    "recall-0.15": 0.995907,
+    "recall-0.25": 0.999318,
+    "recall-0.5": 0.999318,
+    "num_labels": 1466
+  },
+  "knee_left": {
+    "count": 1464,
+    "mean": 0.031951,
+    "median": 0.028307,
+    "std": 0.018777,
+    "sem": 0.000491,
+    "min": 0.002743,
+    "max": 0.153637,
+    "recall-0.025": 0.417065,
+    "recall-0.05": 0.865529,
+    "recall-0.1": 0.990444,
+    "recall-0.15": 0.997952,
+    "recall-0.25": 0.999317,
+    "recall-0.5": 0.999317,
+    "num_labels": 1465
+  },
+  "knee_right": {
+    "count": 1458,
+    "mean": 0.034502,
+    "median": 0.030849,
+    "std": 0.019855,
     "sem": 0.00052,
     "min": 0.002456,
     "max": 0.205948,
     "recall-0.025": 0.374914,
     "recall-0.05": 0.818369,
-    "recall-0.1": 0.986292,
-    "recall-0.15": 0.997944,
-    "recall-0.25": 0.998629,
-    "recall-0.5": 0.998629,
+    "recall-0.1": 0.986977,
+    "recall-0.15": 0.998629,
+    "recall-0.25": 0.999315,
+    "recall-0.5": 0.999315,
     "num_labels": 1459
   },
   "ankle_left": {
-    "count": 1459,
-    "mean": 0.054458,
-    "median": 0.033123,
-    "std": 0.059469,
-    "sem": 0.001557,
+    "count": 1461,
+    "mean": 0.054406,
+    "median": 0.033161,
+    "std": 0.058541,
+    "sem": 0.001532,
     "min": 0.002262,
     "max": 0.458662,
-    "recall-0.025": 0.367054,
-    "recall-0.05": 0.663021,
+    "recall-0.025": 0.36637,
+    "recall-0.05": 0.660971,
     "recall-0.1": 0.856459,
-    "recall-0.15": 0.920711,
-    "recall-0.25": 0.978127,
-    "recall-0.5": 0.997266,
+    "recall-0.15": 0.922078,
+    "recall-0.25": 0.980861,
+    "recall-0.5": 0.998633,
     "num_labels": 1463
   },
   "ankle_right": {
-    "count": 1455,
-    "mean": 0.049672,
-    "median": 0.029994,
-    "std": 0.06081,
-    "sem": 0.001595,
+    "count": 1457,
+    "mean": 0.050245,
+    "median": 0.030058,
+    "std": 0.06195,
+    "sem": 0.001624,
     "min": 0.001983,
     "max": 0.48623,
-    "recall-0.025": 0.381507,
-    "recall-0.05": 0.75274,
-    "recall-0.1": 0.887671,
-    "recall-0.15": 0.933562,
+    "recall-0.025": 0.380822,
+    "recall-0.05": 0.750685,
+    "recall-0.1": 0.886301,
+    "recall-0.15": 0.932877,
     "recall-0.25": 0.971918,
-    "recall-0.5": 0.996575,
+    "recall-0.5": 0.997945,
     "num_labels": 1460
   },
   "joint_recalls": {
     "num_labels": 18990,
-    "recall-0.025": 0.62823,
+    "recall-0.025": 0.62828,
     "recall-0.05": 0.89073,
-    "recall-0.1": 0.9712,
-    "recall-0.15": 0.98441,
-    "recall-0.25": 0.99384,
-    "recall-0.5": 0.99747
+    "recall-0.1": 0.97199,
+    "recall-0.15": 0.98531,
+    "recall-0.25": 0.99505,
+    "recall-0.5": 0.99884
   }
 }
 {
   "total_parts": 20444,
-  "correct_parts": 20328,
-  "pcp": 0.994326
+  "correct_parts": 20350,
+  "pcp": 0.995402
 }
 ```
 
@@ -1972,63 +1979,64 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0918391,
-  "demosaicing": 0.00234244,
-  "avg_time_2d": 0.032068,
-  "avg_time_3d": 0.000509022,
-  "fps": 28.6373
+  "img_loading": 0.0909658,
+  "demosaicing": 0.00242828,
+  "avg_time_2d": 0.0324017,
+  "avg_time_3d": 0.00050742,
+  "time_tracks": 2.20957e-06,
+  "fps": 28.2969
 }
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@@ -2208,15 +2216,15 @@ Results of the model in various experiments on different datasets. \
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@@ -2224,26 +2232,26 @@ Results of the model in various experiments on different datasets. \
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@@ -2259,63 +2267,64 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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@@ -2511,26 +2520,26 @@ Results of the model in various experiments on different datasets. \
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@@ -2550,6 +2559,7 @@ Results of the model in various experiments on different datasets. \
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 }
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 ```json
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 {
   "total_parts": 10920,
-  "correct_parts": 10776,
-  "pcp": 0.986813
+  "correct_parts": 10806,
+  "pcp": 0.98956
 }
 ```
 
@@ -3120,26 +3131,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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-  "avg_time_2d": 0.0182223,
-  "avg_time_3d": 0.000181552,
-  "fps": 47.2343
+  "img_loading": 0.109176,
+  "demosaicing": 0.00278284,
+  "avg_time_2d": 0.0182905,
+  "avg_time_3d": 0.000181146,
+  "time_tracks": 9.5166e-07,
+  "fps": 47.0467
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-  "post_time": 7.96508e-06,
-  "convert_time": 1.33171e-07,
-  "total_time": 0.000170749
+  "init_time": 3.0223e-06,
+  "undistort_time": 1.5911e-05,
+  "project_time": 2.70853e-06,
+  "match_time": 9.89257e-06,
+  "pairs_time": 5.23378e-06,
+  "pair_scoring_time": 4.18337e-05,
+  "grouping_time": 1.22786e-05,
+  "full_time": 4.92026e-05,
+  "merge_time": 2.1051e-05,
+  "post_time": 8.00654e-06,
+  "convert_time": 1.46814e-07,
+  "total_time": 0.000169521
 }
 {
   "person_nums": {
@@ -3158,9 +3170,9 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 630,
-    "mean": 0.052822,
+    "mean": 0.052814,
     "median": 0.048901,
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+    "std": 0.017799,
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     "min": 0.030026,
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@@ -3172,8 +3184,8 @@ Results of the model in various experiments on different datasets. \
     "recall-0.5": 1.0,
     "num_labels": 630,
     "ap-0.025": 0.0,
-    "ap-0.05": 0.363228,
-    "ap-0.1": 0.948697,
+    "ap-0.05": 0.36398,
+    "ap-0.1": 0.948533,
     "ap-0.15": 1.0,
     "ap-0.25": 1.0,
     "ap-0.5": 1.0
@@ -3276,10 +3288,10 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_right": {
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-    "mean": 0.050742,
+    "mean": 0.050698,
     "median": 0.046406,
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+    "std": 0.023717,
+    "sem": 0.000949,
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@@ -3372,14 +3384,14 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_right": {
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@@ -3413,6 +3425,7 @@ Results of the model in various experiments on different datasets. \
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   "avg_time_2d": 0.00831252,
   "avg_time_3d": 3.5924e-05,
+  "time_tracks": 0,
   "fps": 111.382
 }
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@@ -3700,6 +3713,7 @@ Results of the model in various experiments on different datasets. \
   "demosaicing": 0.000593971,
   "avg_time_2d": 0.0114823,
   "avg_time_3d": 0.000122483,
+  "time_tracks": 0,
   "fps": 81.9754
 }
 {
@@ -5985,286 +5999,287 @@ Results of the model in various experiments on different datasets. \
 
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+  "avg_time_3d": 0.000302427,
+  "time_tracks": 2.3222e-06,
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   "joint_recalls": {
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 }
 {
   "total_parts": 5600,
-  "correct_parts": 5443,
-  "pcp": 0.971964
+  "correct_parts": 5457,
+  "pcp": 0.974464
 }
 ```
 
@@ -6272,26 +6287,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.011134,
-  "avg_time_2d": 0.0239827,
-  "avg_time_3d": 0.000251315,
-  "fps": 28.2742
+  "img_loading": 0.278285,
+  "demosaicing": 0.0110585,
+  "avg_time_2d": 0.0239786,
+  "avg_time_3d": 0.000251731,
+  "time_tracks": 9.95126e-07,
+  "fps": 28.3367
 }
 {
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-  "post_time": 8.43239e-06,
-  "convert_time": 1.34463e-07,
-  "total_time": 0.0002427
+  "init_time": 3.60429e-06,
+  "undistort_time": 1.8677e-05,
+  "project_time": 3.7664e-06,
+  "match_time": 1.28861e-05,
+  "pairs_time": 9.90012e-06,
+  "pair_scoring_time": 6.27622e-05,
+  "grouping_time": 1.80751e-05,
+  "full_time": 7.07869e-05,
+  "merge_time": 3.37148e-05,
+  "post_time": 8.32524e-06,
+  "convert_time": 1.54793e-07,
+  "total_time": 0.000242887
 }
 {
   "person_nums": {
@@ -6559,26 +6575,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.0124074,
-  "avg_time_2d": 0.0289188,
-  "avg_time_3d": 0.000433233,
-  "fps": 23.9467
+  "img_loading": 0.299902,
+  "demosaicing": 0.0126655,
+  "avg_time_2d": 0.0290299,
+  "avg_time_3d": 0.000444933,
+  "time_tracks": 2.21974e-06,
+  "fps": 23.729
 }
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-  "post_time": 9.86665e-06,
-  "convert_time": 1.82283e-07,
-  "total_time": 0.000418932
+  "init_time": 4.89887e-06,
+  "undistort_time": 2.5718e-05,
+  "project_time": 6.0061e-06,
+  "match_time": 2.35875e-05,
+  "pairs_time": 2.54117e-05,
+  "pair_scoring_time": 0.000109867,
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+  "merge_time": 5.94845e-05,
+  "post_time": 1.05036e-05,
+  "convert_time": 2.23861e-07,
+  "total_time": 0.000429098
 }
 {
   "person_nums": {
@@ -6846,63 +6863,64 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.0111053,
-  "avg_time_2d": 0.0281809,
-  "avg_time_3d": 0.000408797,
-  "fps": 25.1921
+  "img_loading": 0.292579,
+  "demosaicing": 0.0110868,
+  "avg_time_2d": 0.0281903,
+  "avg_time_3d": 0.000412008,
+  "time_tracks": 2.30442e-06,
+  "fps": 25.1944
 }
 {
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-  "match_time": 2.30387e-05,
-  "pairs_time": 2.23814e-05,
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-  "post_time": 9.98878e-06,
-  "convert_time": 1.80464e-07,
-  "total_time": 0.000396605
+  "init_time": 4.04995e-06,
+  "undistort_time": 2.45463e-05,
+  "project_time": 5.12282e-06,
+  "match_time": 2.29104e-05,
+  "pairs_time": 2.32846e-05,
+  "pair_scoring_time": 0.00010895,
+  "grouping_time": 5.09008e-05,
+  "full_time": 0.000103292,
+  "merge_time": 4.60682e-05,
+  "post_time": 1.02196e-05,
+  "convert_time": 2.05991e-07,
+  "total_time": 0.000399788
 }
 {
   "person_nums": {
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     "total_labels": 330,
-    "total_preds": 438,
+    "total_preds": 440,
     "considered_empty": 0,
     "valid_preds": 330,
-    "invalid_preds": 108,
+    "invalid_preds": 110,
     "missing": 0,
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-    "precision": 0.75342,
+    "invalid_fraction": 0.25,
+    "precision": 0.75,
     "recall": 1.0,
-    "f1": 0.85938,
-    "non_empty": 438
+    "f1": 0.85714,
+    "non_empty": 440
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   "mpjpe": {
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-    "sem": 0.000864,
+    "mean": 0.040993,
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     "min": 0.018223,
     "max": 0.119589,
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+    "recall-0.025": 0.09697,
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-    "ap-0.25": 0.765149,
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+    "ap-0.025": 0.011594,
+    "ap-0.05": 0.506581,
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+    "ap-0.15": 0.761225,
+    "ap-0.25": 0.761225,
+    "ap-0.5": 0.761225
   },
   "head": {
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@@ -6986,16 +7004,16 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
     "count": 329,
-    "mean": 0.046373,
+    "mean": 0.046821,
     "median": 0.039868,
-    "std": 0.031237,
-    "sem": 0.001725,
+    "std": 0.032923,
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     "recall-0.05": 0.624242,
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+    "recall-0.1": 0.936364,
+    "recall-0.15": 0.981818,
     "recall-0.25": 0.99697,
     "recall-0.5": 0.99697,
     "num_labels": 330
@@ -7082,50 +7100,50 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_left": {
     "count": 330,
-    "mean": 0.030999,
-    "median": 0.025737,
-    "std": 0.022585,
-    "sem": 0.001245,
+    "mean": 0.032268,
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+    "sem": 0.001607,
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   "joint_recalls": {
     "num_labels": 4290,
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+    "recall-0.25": 0.99907,
     "recall-0.5": 0.99977
   }
 }
 {
   "total_parts": 4620,
-  "correct_parts": 4603,
-  "pcp": 0.99632
+  "correct_parts": 4600,
+  "pcp": 0.995671
 }
 ```
 
@@ -7133,286 +7151,287 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.0177444,
-  "avg_time_2d": 0.0511469,
-  "avg_time_3d": 0.000936227,
-  "fps": 14.321
+  "img_loading": 0.432763,
+  "demosaicing": 0.0178295,
+  "avg_time_2d": 0.0512937,
+  "avg_time_3d": 0.000928159,
+  "time_tracks": 3.54476e-06,
+  "fps": 14.2745
 }
 {
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-  "undistort_time": 5.17806e-05,
-  "project_time": 9.25822e-06,
-  "match_time": 3.9928e-05,
-  "pairs_time": 7.50967e-05,
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-  "post_time": 1.11279e-05,
-  "convert_time": 2.07289e-07,
-  "total_time": 0.000918031
+  "init_time": 6.75621e-06,
+  "undistort_time": 5.12374e-05,
+  "project_time": 8.89762e-06,
+  "match_time": 3.95005e-05,
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+  "post_time": 1.10982e-05,
+  "convert_time": 2.25504e-07,
+  "total_time": 0.000911537
 }
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-    "median": 0.026922,
-    "std": 0.01566,
-    "sem": 0.000715,
+    "count": 483,
+    "mean": 0.029716,
+    "median": 0.026997,
+    "std": 0.015822,
+    "sem": 0.000721,
     "min": 0.002764,
     "max": 0.107294,
     "recall-0.025": 0.454545,
     "recall-0.05": 0.882231,
-    "recall-0.1": 0.991736,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.1": 0.995868,
+    "recall-0.15": 0.997934,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "elbow_right": {
-    "count": 481,
-    "mean": 0.030148,
-    "median": 0.025142,
-    "std": 0.019918,
-    "sem": 0.000909,
+    "count": 483,
+    "mean": 0.030195,
+    "median": 0.025171,
+    "std": 0.019893,
+    "sem": 0.000906,
     "min": 0.001453,
     "max": 0.135761,
     "recall-0.025": 0.495868,
-    "recall-0.05": 0.869835,
-    "recall-0.1": 0.977273,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.05": 0.873967,
+    "recall-0.1": 0.981405,
+    "recall-0.15": 0.997934,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "wrist_left": {
-    "count": 481,
-    "mean": 0.033997,
-    "median": 0.028323,
-    "std": 0.022891,
-    "sem": 0.001045,
+    "count": 483,
+    "mean": 0.034414,
+    "median": 0.028426,
+    "std": 0.023744,
+    "sem": 0.001081,
     "min": 0.002816,
     "max": 0.208094,
     "recall-0.025": 0.404959,
     "recall-0.05": 0.822314,
     "recall-0.1": 0.971074,
-    "recall-0.15": 0.991736,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.15": 0.995868,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "wrist_right": {
-    "count": 481,
-    "mean": 0.033888,
-    "median": 0.028374,
-    "std": 0.026695,
-    "sem": 0.001218,
+    "count": 483,
+    "mean": 0.034014,
+    "median": 0.028476,
+    "std": 0.026712,
+    "sem": 0.001217,
     "min": 0.00351,
     "max": 0.284667,
     "recall-0.025": 0.390496,
     "recall-0.05": 0.849174,
-    "recall-0.1": 0.97314,
-    "recall-0.15": 0.989669,
-    "recall-0.25": 0.989669,
-    "recall-0.5": 0.993802,
+    "recall-0.1": 0.977273,
+    "recall-0.15": 0.993802,
+    "recall-0.25": 0.993802,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "hip_left": {
-    "count": 481,
-    "mean": 0.034059,
-    "median": 0.030974,
-    "std": 0.016804,
-    "sem": 0.000767,
+    "count": 483,
+    "mean": 0.03467,
+    "median": 0.031172,
+    "std": 0.019736,
+    "sem": 0.000899,
     "min": 0.002885,
-    "max": 0.112591,
+    "max": 0.248625,
     "recall-0.025": 0.305785,
     "recall-0.05": 0.842975,
     "recall-0.1": 0.989669,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.15": 0.995868,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "hip_right": {
-    "count": 481,
-    "mean": 0.037366,
-    "median": 0.032222,
-    "std": 0.023149,
-    "sem": 0.001057,
+    "count": 483,
+    "mean": 0.038046,
+    "median": 0.032255,
+    "std": 0.025653,
+    "sem": 0.001168,
     "min": 0.003771,
-    "max": 0.144196,
+    "max": 0.258232,
     "recall-0.025": 0.31405,
     "recall-0.05": 0.799587,
     "recall-0.1": 0.966942,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.15": 0.995868,
+    "recall-0.25": 0.995868,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "knee_left": {
-    "count": 481,
-    "mean": 0.021056,
-    "median": 0.016878,
-    "std": 0.015358,
-    "sem": 0.000701,
+    "count": 483,
+    "mean": 0.021558,
+    "median": 0.017019,
+    "std": 0.017418,
+    "sem": 0.000793,
     "min": 0.002951,
-    "max": 0.18051,
+    "max": 0.185898,
     "recall-0.025": 0.721074,
     "recall-0.05": 0.950413,
-    "recall-0.1": 0.991736,
-    "recall-0.15": 0.991736,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.1": 0.993802,
+    "recall-0.15": 0.993802,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "knee_right": {
-    "count": 481,
-    "mean": 0.023866,
-    "median": 0.019475,
-    "std": 0.01567,
-    "sem": 0.000715,
+    "count": 483,
+    "mean": 0.024245,
+    "median": 0.01952,
+    "std": 0.016893,
+    "sem": 0.000769,
     "min": 0.001804,
-    "max": 0.101887,
+    "max": 0.154682,
     "recall-0.025": 0.654959,
     "recall-0.05": 0.923554,
-    "recall-0.1": 0.991736,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.1": 0.993802,
+    "recall-0.15": 0.995868,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "ankle_left": {
-    "count": 481,
-    "mean": 0.021426,
-    "median": 0.017845,
-    "std": 0.015273,
-    "sem": 0.000697,
+    "count": 483,
+    "mean": 0.022242,
+    "median": 0.017863,
+    "std": 0.01983,
+    "sem": 0.000903,
     "min": 0.001647,
-    "max": 0.158699,
+    "max": 0.231289,
     "recall-0.025": 0.714876,
     "recall-0.05": 0.954545,
     "recall-0.1": 0.987603,
     "recall-0.15": 0.991736,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "ankle_right": {
-    "count": 481,
-    "mean": 0.021895,
-    "median": 0.018026,
-    "std": 0.013532,
-    "sem": 0.000618,
+    "count": 483,
+    "mean": 0.022243,
+    "median": 0.018055,
+    "std": 0.014583,
+    "sem": 0.000664,
     "min": 0.001986,
-    "max": 0.090749,
+    "max": 0.122528,
     "recall-0.025": 0.708678,
     "recall-0.05": 0.93595,
-    "recall-0.1": 0.993802,
-    "recall-0.15": 0.993802,
-    "recall-0.25": 0.993802,
-    "recall-0.5": 0.993802,
+    "recall-0.1": 0.995868,
+    "recall-0.15": 0.997934,
+    "recall-0.25": 0.997934,
+    "recall-0.5": 0.997934,
     "num_labels": 484
   },
   "joint_recalls": {
     "num_labels": 6292,
     "recall-0.025": 0.51081,
-    "recall-0.05": 0.87858,
-    "recall-0.1": 0.98411,
-    "recall-0.15": 0.99285,
-    "recall-0.25": 0.99332,
-    "recall-0.5": 0.9938
+    "recall-0.05": 0.87889,
+    "recall-0.1": 0.98665,
+    "recall-0.15": 0.99619,
+    "recall-0.25": 0.99746,
+    "recall-0.5": 0.99793
   }
 }
 {
   "total_parts": 6776,
-  "correct_parts": 6730,
-  "pcp": 0.993211
+  "correct_parts": 6755,
+  "pcp": 0.996901
 }
 ```
 
@@ -7420,26 +7439,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.413332,
-  "demosaicing": 0.0175982,
-  "avg_time_2d": 0.0438098,
-  "avg_time_3d": 0.000727766,
-  "fps": 16.0938
+  "img_loading": 0.425309,
+  "demosaicing": 0.0175828,
+  "avg_time_2d": 0.0439122,
+  "avg_time_3d": 0.000732078,
+  "time_tracks": 2.60839e-06,
+  "fps": 16.0695
 }
 {
   "triangulator_calls": 183,
-  "init_time": 5.79021e-06,
-  "undistort_time": 4.21408e-05,
-  "project_time": 8.16923e-06,
-  "match_time": 3.26939e-05,
-  "pairs_time": 5.31224e-05,
-  "pair_scoring_time": 0.000196534,
-  "grouping_time": 7.74538e-05,
-  "full_time": 0.000190952,
-  "merge_time": 9.15214e-05,
-  "post_time": 1.07165e-05,
-  "convert_time": 2.0876e-07,
-  "total_time": 0.000709537
+  "init_time": 5.78507e-06,
+  "undistort_time": 4.25049e-05,
+  "project_time": 8.30154e-06,
+  "match_time": 3.30885e-05,
+  "pairs_time": 5.5239e-05,
+  "pair_scoring_time": 0.000196453,
+  "grouping_time": 7.68858e-05,
+  "full_time": 0.000192775,
+  "merge_time": 9.31284e-05,
+  "post_time": 1.08601e-05,
+  "convert_time": 2.36311e-07,
+  "total_time": 0.000715494
 }
 {
   "person_nums": {
@@ -7707,26 +7727,27 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.626226,
-  "demosaicing": 0.0268474,
-  "avg_time_2d": 0.0513508,
-  "avg_time_3d": 0.000611629,
-  "fps": 12.6888
+  "img_loading": 0.671268,
+  "demosaicing": 0.0270076,
+  "avg_time_2d": 0.051466,
+  "avg_time_3d": 0.000617507,
+  "time_tracks": 1.15879e-06,
+  "fps": 12.6435
 }
 {
   "triangulator_calls": 181,
-  "init_time": 7.41259e-06,
-  "undistort_time": 3.17885e-05,
-  "project_time": 7.35977e-06,
-  "match_time": 1.57646e-05,
-  "pairs_time": 2.24304e-05,
-  "pair_scoring_time": 0.000162925,
-  "grouping_time": 5.9874e-05,
-  "full_time": 0.000175241,
-  "merge_time": 8.98064e-05,
-  "post_time": 7.85762e-06,
-  "convert_time": 1.16287e-07,
-  "total_time": 0.000580813
+  "init_time": 7.98041e-06,
+  "undistort_time": 3.16803e-05,
+  "project_time": 7.51399e-06,
+  "match_time": 1.58883e-05,
+  "pairs_time": 2.35366e-05,
+  "pair_scoring_time": 0.000162144,
+  "grouping_time": 5.94076e-05,
+  "full_time": 0.000175584,
+  "merge_time": 9.06647e-05,
+  "post_time": 8.08327e-06,
+  "convert_time": 1.40492e-07,
+  "total_time": 0.000582859
 }
 {
   "person_nums": {
diff --git a/rpt/tracker.hpp b/rpt/tracker.hpp
new file mode 100644
index 0000000..d8049da
--- /dev/null
+++ b/rpt/tracker.hpp
@@ -0,0 +1,319 @@
+#pragma once
+
+#include <array>
+#include <string>
+#include <vector>
+#include <algorithm>
+#include <limits>
+#include <cmath>
+#include <iostream>
+
+// =================================================================================================
+
+struct Track
+{
+    std::vector<std::vector<std::array<float, 4>>> core_poses;
+    std::vector<std::vector<std::array<float, 4>>> full_poses;
+
+    std::vector<double> timestamps;
+    size_t id;
+};
+
+// =================================================================================================
+
+class PoseTracker
+{
+public:
+    PoseTracker(float max_movement_speed, float max_distance);
+
+    std::vector<std::tuple<size_t, std::vector<std::array<float, 4>>>> track_poses(
+        const std::vector<std::vector<std::array<float, 4>>> &poses_3d,
+        const std::vector<std::string> &joint_names,
+        const double timestamp);
+
+    void reset();
+
+private:
+    float max_distance;
+    float max_movement_speed;
+    size_t history_size = 3;
+
+    std::vector<double> timestamps;
+    std::vector<Track> pose_tracks;
+
+    const std::vector<std::string> core_joints = {
+        "shoulder_left",
+        "shoulder_right",
+        "hip_left",
+        "hip_right",
+        "elbow_left",
+        "elbow_right",
+        "knee_left",
+        "knee_right",
+        "wrist_left",
+        "wrist_right",
+        "ankle_left",
+        "ankle_right",
+    };
+
+    std::tuple<int, float> match_to_track(const std::vector<std::array<float, 4>> &core_pose_3d);
+
+    std::vector<std::array<float, 4>> refine_pose(const Track &track);
+};
+
+// =================================================================================================
+// =================================================================================================
+
+PoseTracker::PoseTracker(float max_movement_speed, float max_distance)
+{
+    this->max_movement_speed = max_movement_speed;
+    this->max_distance = max_distance;
+}
+
+// =================================================================================================
+
+void PoseTracker::reset()
+{
+    pose_tracks.clear();
+    timestamps.clear();
+}
+
+// =================================================================================================
+
+std::vector<std::tuple<size_t, std::vector<std::array<float, 4>>>> PoseTracker::track_poses(
+    const std::vector<std::vector<std::array<float, 4>>> &poses_3d,
+    const std::vector<std::string> &joint_names,
+    const double timestamp)
+{
+    // Extract core joints
+    std::vector<size_t> core_joint_idx;
+    for (const auto &joint : core_joints)
+    {
+        auto it = std::find(joint_names.begin(), joint_names.end(), joint);
+        core_joint_idx.push_back(std::distance(joint_names.begin(), it));
+    }
+    std::vector<std::vector<std::array<float, 4>>> core_poses;
+    core_poses.resize(poses_3d.size());
+    for (size_t i = 0; i < poses_3d.size(); ++i)
+    {
+        core_poses[i].resize(core_joint_idx.size());
+        for (size_t j = 0; j < core_joint_idx.size(); ++j)
+        {
+            for (size_t k = 0; k < 4; ++k)
+            {
+                core_poses[i][j][k] = poses_3d[i][core_joint_idx[j]][k];
+            }
+        }
+    }
+
+    // Match core poses to tracks
+    std::vector<std::tuple<size_t, int, float>> matches;
+    for (size_t i = 0; i < core_poses.size(); ++i)
+    {
+        auto [track_idx, distance_sq] = match_to_track(core_poses[i]);
+        matches.emplace_back(i, track_idx, distance_sq);
+    }
+    std::sort(matches.begin(), matches.end(),
+              [](const auto &a, const auto &b)
+              { return std::get<2>(a) < std::get<2>(b); });
+
+    // If track is matched multiple times, only add the best and create new tracks for the rest
+    std::vector<bool> used(pose_tracks.size(), false);
+    for (size_t i = 0; i < matches.size(); ++i)
+    {
+        auto [pose_idx, track_idx, distance_sq] = matches[i];
+        if (track_idx != -1 && !used[track_idx])
+        {
+            used[track_idx] = true;
+        }
+        else
+        {
+            std::get<1>(matches[i]) = -1;
+        }
+    }
+
+    // Update tracks
+    for (size_t i = 0; i < matches.size(); ++i)
+    {
+        auto [pose_idx, track_idx, distance_sq] = matches[i];
+        if (track_idx == -1)
+        {
+            // Create a new track
+            Track new_track;
+            new_track.core_poses.push_back(core_poses[pose_idx]);
+            new_track.full_poses.push_back(poses_3d[pose_idx]);
+            new_track.timestamps.push_back(timestamp);
+            new_track.id = pose_tracks.size();
+            pose_tracks.push_back(new_track);
+        }
+        else
+        {
+            // Update existing track
+            auto &track = pose_tracks[track_idx];
+            track.core_poses.push_back(core_poses[pose_idx]);
+            track.full_poses.push_back(poses_3d[pose_idx]);
+            track.timestamps.push_back(timestamp);
+        }
+    }
+
+    // Remove old tracks
+    timestamps.push_back(timestamp);
+    if (timestamps.size() > history_size)
+    {
+        timestamps.erase(timestamps.begin());
+    }
+    double max_age = timestamps.front();
+    for (size_t i = 0; i < pose_tracks.size();)
+    {
+        auto &track = pose_tracks[i];
+        double last_timestamp = track.timestamps.back();
+        if (last_timestamp < max_age)
+        {
+            pose_tracks.erase(pose_tracks.begin() + i);
+        }
+        else
+        {
+            ++i;
+        }
+    }
+
+    // Remove old poses from tracks
+    for (auto &track : pose_tracks)
+    {
+        while (track.core_poses.size() > history_size)
+        {
+            track.core_poses.erase(track.core_poses.begin());
+            track.full_poses.erase(track.full_poses.begin());
+            track.timestamps.erase(track.timestamps.begin());
+        }
+    }
+
+    // Refine poses
+    std::vector<std::tuple<size_t, std::vector<std::array<float, 4>>>> tracked_poses;
+    for (size_t i = 0; i < pose_tracks.size(); ++i)
+    {
+        auto &track = pose_tracks[i];
+        if (track.core_poses.size() > 0)
+        {
+            std::vector<std::array<float, 4>> refined_pose = refine_pose(track);
+            tracked_poses.emplace_back(track.id, refined_pose);
+        }
+    }
+
+    return tracked_poses;
+}
+
+// =================================================================================================
+
+std::tuple<int, float> PoseTracker::match_to_track(const std::vector<std::array<float, 4>> &core_pose_3d)
+{
+    int best_track = -1;
+    float best_distance_sq = max_distance * max_distance;
+
+    for (size_t i = 0; i < pose_tracks.size(); ++i)
+    {
+        const auto &track = pose_tracks[i];
+        if (track.core_poses.size() == 0)
+        {
+            continue;
+        }
+
+        // Calculate distance to the last pose in the track
+        const auto &last_pose = track.core_poses.back();
+        float distance_sq = 0.0;
+        for (size_t j = 0; j < core_pose_3d.size(); ++j)
+        {
+            float dx = core_pose_3d[j][0] - last_pose[j][0];
+            float dy = core_pose_3d[j][1] - last_pose[j][1];
+            float dz = core_pose_3d[j][2] - last_pose[j][2];
+            distance_sq += dx * dx + dy * dy + dz * dz;
+        }
+        distance_sq /= core_pose_3d.size();
+
+        if (distance_sq < best_distance_sq)
+        {
+            best_distance_sq = distance_sq;
+            best_track = static_cast<int>(i);
+        }
+    }
+
+    return {best_track, best_distance_sq};
+}
+
+// =================================================================================================
+
+std::vector<std::array<float, 4>> PoseTracker::refine_pose(const Track &track)
+{
+    // Restrict maximum movement by physical constraints, by clipping the pose to the maximum
+    // movement distance from one of the track's history poses
+    //
+    // While advanced sensor filtering techniques, like using a Kalman-Filter, might improve the
+    // average accuracy of the pose, they introduce update delays on fast movement changes. For
+    // example, if a person stands still for a while and then suddenly moves, the first few frames
+    // will likely be treated as outliers, since the filter will not be able to adapt fast enough.
+    // This behaviour is not desired in a real-time critical applications, where the pose needs to
+    // be updated to the real physical position of the person as fast as possible. Therefore, only
+    // the movement speed is limited here.
+
+    if (track.core_poses.size() < 2)
+    {
+        return track.full_poses.back();
+    }
+
+    // Calculate maximum possible movement distance from each history pose
+    std::vector<float> max_movement_dists_sq;
+    max_movement_dists_sq.resize(track.core_poses.size() - 1);
+    double last_timestamp = track.timestamps.back();
+    for (size_t i = 0; i < track.core_poses.size() - 1; ++i)
+    {
+        double ts = track.timestamps[i];
+        float max_movement = max_movement_speed * (last_timestamp - ts);
+        max_movement_dists_sq[i] = max_movement * max_movement;
+    }
+
+    // Clip joint if required
+    std::vector<std::array<float, 4>> refined_pose = track.full_poses.back();
+    for (size_t i = 0; i < refined_pose.size(); ++i)
+    {
+        float min_dist_sq = std::numeric_limits<float>::infinity();
+        size_t closest_idx = 0;
+        bool clip = true;
+
+        for (size_t j = 0; j < max_movement_dists_sq.size(); ++j)
+        {
+
+            float dx = refined_pose[i][0] - track.full_poses[j][i][0];
+            float dy = refined_pose[i][1] - track.full_poses[j][i][1];
+            float dz = refined_pose[i][2] - track.full_poses[j][i][2];
+            float dist_sq = dx * dx + dy * dy + dz * dz;
+            if (dist_sq < min_dist_sq)
+            {
+                min_dist_sq = dist_sq;
+                closest_idx = j;
+            }
+            if (dist_sq <= max_movement_dists_sq[j])
+            {
+                clip = false;
+                break;
+            }
+        }
+
+        if (clip)
+        {
+            float dist_sq = min_dist_sq;
+            float scale = max_movement_dists_sq[closest_idx] / dist_sq;
+
+            float dx = refined_pose[i][0] - track.full_poses[closest_idx][i][0];
+            float dy = refined_pose[i][1] - track.full_poses[closest_idx][i][1];
+            float dz = refined_pose[i][2] - track.full_poses[closest_idx][i][2];
+            refined_pose[i][0] = track.full_poses[closest_idx][i][0] + dx * scale;
+            refined_pose[i][1] = track.full_poses[closest_idx][i][1] + dy * scale;
+            refined_pose[i][2] = track.full_poses[closest_idx][i][2] + dz * scale;
+
+            // Set confidence to a low value if the joint is clipped
+            refined_pose[i][3] = 0.1;
+        }
+    }
+
+    return refined_pose;
+}
diff --git a/scripts/test_skelda_dataset.cpp b/scripts/test_skelda_dataset.cpp
index 37b8626..e93ce50 100644
--- a/scripts/test_skelda_dataset.cpp
+++ b/scripts/test_skelda_dataset.cpp
@@ -17,6 +17,7 @@ using json = nlohmann::json;
 
 #include "/RapidPoseTriangulation/rpt/camera.hpp"
 #include "/RapidPoseTriangulation/rpt/interface.hpp"
+#include "/RapidPoseTriangulation/rpt/tracker.hpp"
 #include "/RapidPoseTriangulation/scripts/utils_2d_pose.hpp"
 #include "/RapidPoseTriangulation/scripts/utils_pipeline.hpp"
 
@@ -121,6 +122,9 @@ int main(int argc, char **argv)
     const float min_match_score = config["min_match_score"];
     const size_t min_group_size = config["min_group_size"];
     const int take_interval = config["take_interval"];
+    const float ifps = config["fps"];
+    const float max_movement_speed = config["max_movement_speed"];
+    const float max_track_distance = config["max_track_distance"];
 
     // Load 2D model
     bool use_wb = utils_pipeline::use_whole_body(whole_body);
@@ -128,9 +132,11 @@ int main(int argc, char **argv)
         std::make_unique<utils_2d_pose::PosePredictor>(
             use_wb, min_bbox_score, min_bbox_area, batch_poses);
 
-    // Load 3D model
+    // Load 3D models
     std::unique_ptr<Triangulator> tri_model = std::make_unique<Triangulator>(
         min_match_score, min_group_size);
+    std::unique_ptr<PoseTracker> pose_tracker = std::make_unique<PoseTracker>(
+        max_movement_speed, max_track_distance);
 
     // Timers
     size_t time_count = dataset.size();
@@ -138,10 +144,12 @@ int main(int argc, char **argv)
     std::vector<double> times_debayer;
     std::vector<double> times_pose2d;
     std::vector<double> times_pose3d;
+    std::vector<double> times_tracks;
     times_image.reserve(time_count);
     times_debayer.reserve(time_count);
     times_pose2d.reserve(time_count);
     times_pose3d.reserve(time_count);
+    times_tracks.reserve(time_count);
     size_t print_steps = (size_t)std::floor((float)time_count / 100.0f);
     print_steps = std::max((size_t)1, print_steps);
 
@@ -214,6 +222,7 @@ int main(int argc, char **argv)
         {
             // Reset last poses if scene changes
             tri_model->reset();
+            pose_tracker->reset();
             old_scene = item["scene"];
         }
 
@@ -241,6 +250,27 @@ int main(int argc, char **argv)
         elapsed = std::chrono::high_resolution_clock::now() - stime;
         times_pose3d.push_back(elapsed.count());
 
+        if (ifps <= 0)
+        {
+            // Disable pose tracking if frame rate is too low
+            times_tracks.push_back(0.0);
+        }
+        else
+        {
+            stime = std::chrono::high_resolution_clock::now();
+            double ts = ((int)item["index"]) / ifps;
+            auto pose_tracks = pose_tracker->track_poses(poses_3d, joint_names_2d, ts);
+            std::vector<std::vector<std::array<float, 4>>> poses_3d_refined;
+            for (size_t j = 0; j < pose_tracks.size(); j++)
+            {
+                auto &pose = std::get<1>(pose_tracks[j]);
+                poses_3d_refined.push_back(pose);
+            }
+            poses_3d = poses_3d_refined;
+            elapsed = std::chrono::high_resolution_clock::now() - stime;
+            times_tracks.push_back(elapsed.count());
+        }
+
         all_poses_3d.push_back(std::move(poses_3d));
         all_ids.push_back(item["id"].get<std::string>());
         old_id = item["index"];
@@ -254,23 +284,27 @@ int main(int argc, char **argv)
     double time_debayer = 0.0;
     double time_pose2d = 0.0;
     double time_pose3d = 0.0;
+    double time_tracks = 0.0;
     for (size_t i = warmup; i < time_count; i++)
     {
         time_image += times_image[i];
         time_debayer += times_debayer[i];
         time_pose2d += times_pose2d[i];
         time_pose3d += times_pose3d[i];
+        time_tracks += times_tracks[i];
     }
     double avg_time_image = time_image / (time_count - warmup);
     double avg_time_debayer = time_debayer / (time_count - warmup);
     double avg_time_pose2d = time_pose2d / (time_count - warmup);
     double avg_time_pose3d = time_pose3d / (time_count - warmup);
-    double fps = 1.0 / (avg_time_debayer + avg_time_pose2d + avg_time_pose3d);
+    double avg_time_tracks = time_tracks / (time_count - warmup);
+    double fps = 1.0 / (avg_time_debayer + avg_time_pose2d + avg_time_pose3d + avg_time_tracks);
     std::cout << "{\n"
               << "  \"img_loading\": " << avg_time_image << ",\n"
               << "  \"demosaicing\": " << avg_time_debayer << ",\n"
               << "  \"avg_time_2d\": " << avg_time_pose2d << ",\n"
               << "  \"avg_time_3d\": " << avg_time_pose3d << ",\n"
+              << "  \"time_tracks\": " << avg_time_tracks << ",\n"
               << "  \"fps\": " << fps << "\n"
               << "}" << std::endl;
     tri_model->print_stats();
diff --git a/scripts/test_skelda_dataset.py b/scripts/test_skelda_dataset.py
index d184f23..688bb52 100644
--- a/scripts/test_skelda_dataset.py
+++ b/scripts/test_skelda_dataset.py
@@ -51,15 +51,27 @@ default_min_group_size = 1
 # If most of the time only one person is in a image, disable it, because it is slightly slower then
 default_batch_poses = True
 
+# Approach speed of EN ISO 13855 with 2000 mm/sec for hand speed
+# and an additional factor to compensate for noise-based jumps
+default_max_movement_speed = 2.0 * 1.5
+
+# The size of an A4 sheet of paper which is assumed to fit between two different persons
+# and additionally the distance a person can move between two frames (here at 10 fps)
+default_max_track_distance = 0.3 + default_max_movement_speed / 10
+
+
 datasets = {
     "human36m": {
         "path": "/datasets/human36m/skelda/pose_test.json",
         "take_interval": 5,
+        "fps": 50,
         "min_match_score": 0.95,
         "min_group_size": 1,
         "min_bbox_score": 0.4,
         "min_bbox_area": 0.1 * 0.1,
         "batch_poses": False,
+        "max_movement_speed": 2.0 * 1.5,
+        "max_track_distance": 0.3 + default_max_movement_speed / (50 / 5),
     },
     "panoptic": {
         "path": "/datasets/panoptic/skelda/test.json",
@@ -69,6 +81,7 @@ datasets = {
         # "cams": ["00_03", "00_06", "00_12", "00_13", "00_23", "00_15", "00_10", "00_21", "00_09", "00_01"],
         # "cams": [],
         "take_interval": 3,
+        "fps": 30,
         "min_match_score": 0.95,
         "use_scenes": ["160906_pizza1", "160422_haggling1", "160906_ian5"],
         "min_group_size": 1,
@@ -77,101 +90,132 @@ datasets = {
         # "min_group_size": 2,
         # "min_group_size": 11,
         "min_bbox_area": 0.05 * 0.05,
+        "max_track_distance": 0.3 + default_max_movement_speed / (30 / 3),
     },
     "mvor": {
         "path": "/datasets/mvor/skelda/all.json",
         "take_interval": 1,
+        "fps": -1,
         "min_match_score": 0.81,
         "min_bbox_score": 0.25,
     },
     "campus": {
         "path": "/datasets/campus/skelda/test.json",
+        "fps": 25,
         "take_interval": 1,
         "min_match_score": 0.91,
         "min_bbox_score": 0.5,
+        "max_track_distance": 0.3 + default_max_movement_speed / 25,
     },
     "shelf": {
         "path": "/datasets/shelf/skelda/test.json",
         "take_interval": 1,
+        "fps": 25,
         "min_match_score": 0.95,
         "min_group_size": 2,
+        "max_track_distance": 0.3 + default_max_movement_speed / 25,
     },
     "ikeaasm": {
         "path": "/datasets/ikeaasm/skelda/test.json",
         "take_interval": 2,
+        "fps": -1,
         "min_match_score": 0.81,
         "min_bbox_score": 0.20,
     },
     "chi3d": {
         "path": "/datasets/chi3d/skelda/all.json",
         "take_interval": 5,
+        "fps": 50,
+        "max_track_distance": 0.3 + default_max_movement_speed / (50 / 5),
     },
     "tsinghua": {
         "path": "/datasets/tsinghua/skelda/test.json",
         "take_interval": 3,
+        "fps": 30,
         "min_match_score": 0.95,
         "min_group_size": 2,
+        "max_track_distance": 0.3 + default_max_movement_speed / (30 / 3),
     },
     "human36m_wb": {
         "path": "/datasets/human36m/skelda/wb/test.json",
         "take_interval": 100,
+        "fps": -1,
         "min_bbox_score": 0.4,
         "batch_poses": False,
     },
     "egohumans_tagging": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "tagging",
         "min_match_score": 0.89,
         "min_group_size": 1,
         "min_bbox_score": 0.2,
         "min_bbox_area": 0.05 * 0.05,
+        "max_movement_speed": 4.0 * 1.5,
+        "max_track_distance": 0.3 + (4.0 * 1.5) / (20 / 2),
     },
     "egohumans_legoassemble": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "legoassemble",
         "min_group_size": 2,
+        "max_track_distance": 0.3 + default_max_movement_speed / (20 / 2),
     },
     "egohumans_fencing": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "fencing",
         "min_group_size": 7,
         "min_bbox_score": 0.5,
         "min_bbox_area": 0.05 * 0.05,
+        "max_track_distance": 0.3 + default_max_movement_speed / (20 / 2),
     },
     "egohumans_basketball": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "basketball",
         "min_group_size": 4,
         "min_bbox_score": 0.25,
         "min_bbox_area": 0.025 * 0.025,
+        "max_movement_speed": 4.0 * 1.5,
+        "max_track_distance": 0.3 + (4.0 * 1.5) / (20 / 2),
     },
     "egohumans_volleyball": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "volleyball",
         "min_match_score": 0.95,
         "min_group_size": 7,
         "min_bbox_score": 0.25,
         "min_bbox_area": 0.05 * 0.05,
+        "max_movement_speed": 4.0 * 1.5,
+        "max_track_distance": 0.3 + (4.0 * 1.5) / (20 / 2),
     },
     "egohumans_badminton": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "badminton",
         "min_group_size": 7,
         "min_bbox_score": 0.25,
         "min_bbox_area": 0.05 * 0.05,
+        "max_movement_speed": 4.0 * 1.5,
+        "max_track_distance": 0.3 + (4.0 * 1.5) / (20 / 2),
     },
     "egohumans_tennis": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
+        "fps": 20,
         "subset": "tennis",
         "min_group_size": 11,
         "min_bbox_area": 0.025 * 0.025,
+        "max_movement_speed": 4.0 * 1.5,
+        "max_track_distance": 0.3 + (4.0 * 1.5) / (20 / 2),
     },
 }
 
@@ -338,6 +382,12 @@ def main():
     min_bbox_score = datasets[dataset_use].get("min_bbox_score", default_min_bbox_score)
     min_bbox_area = datasets[dataset_use].get("min_bbox_area", default_min_bbox_area)
     batch_poses = datasets[dataset_use].get("batch_poses", default_batch_poses)
+    max_movement_speed = datasets[dataset_use].get(
+        "max_movement_speed", default_max_movement_speed
+    )
+    max_track_distance = datasets[dataset_use].get(
+        "max_track_distance", default_max_track_distance
+    )
 
     # Save config
     config_path = tmp_export_dir + "config.json"
@@ -347,8 +397,11 @@ def main():
         "min_bbox_score": min_bbox_score,
         "min_bbox_area": min_bbox_area,
         "batch_poses": batch_poses,
+        "max_movement_speed": max_movement_speed,
+        "max_track_distance": max_track_distance,
         "whole_body": whole_body,
         "take_interval": datasets[dataset_use]["take_interval"],
+        "fps": datasets[dataset_use]["fps"],
     }
     utils_pipeline.save_json(config, config_path)
 
diff --git a/scripts/test_triangulate.py b/scripts/test_triangulate.py
index 04c3885..207ac84 100644
--- a/scripts/test_triangulate.py
+++ b/scripts/test_triangulate.py
@@ -26,6 +26,9 @@ config = {
     "batch_poses": True,
     "whole_body": whole_body,
     "take_interval": 1,
+    "fps": -1,
+    "max_movement_speed": 0,
+    "max_track_distance": 0,
 }
 
 joint_names_2d = utils_pipeline.get_joint_names(whole_body)