diff --git a/extras/jetson/README.md b/extras/jetson/README.md
index 06e8e39..aafb458 100644
--- a/extras/jetson/README.md
+++ b/extras/jetson/README.md
@@ -129,7 +129,7 @@ Tested with a _Jetson AGX Orin Developer Kit_ module.
 - Build docker container:
 
   ```bash
-  docker build --progress=plain -f extras/ros/dockerfile -t rapidposetriangulation_ros .
+  docker build --progress=plain -f extras/ros/dockerfile_2d -t rapidposetriangulation_ros2d .
   ```
 
 - Run and test:
diff --git a/extras/jetson/docker-compose-2d.yml b/extras/jetson/docker-compose-2d.yml
index 64f55be..2310d33 100644
--- a/extras/jetson/docker-compose-2d.yml
+++ b/extras/jetson/docker-compose-2d.yml
@@ -1,10 +1,7 @@
-version: "2.3"
-# runtime: nvidia needs version 2 else change standard runtime at host pc
-
 services:
 
     test_node:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
@@ -15,13 +12,14 @@ services:
             - /tmp/.X11-unix:/tmp/.X11-unix
             - /dev/shm:/dev/shm
         environment:
+            - CAMID
             - DISPLAY
             - QT_X11_NO_MITSHM=1
             - "PYTHONUNBUFFERED=1"
         command: /bin/bash -i -c 'sleep infinity'
 
     estimator:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
diff --git a/extras/mmdeploy/README.md b/extras/mmdeploy/README.md
index 5267815..ab35740 100644
--- a/extras/mmdeploy/README.md
+++ b/extras/mmdeploy/README.md
@@ -61,7 +61,7 @@ mv /mmdeploy/work_dir/end2end.onnx /RapidPoseTriangulation/extras/mmdeploy/expor
 python3 ./tools/deploy.py \
     configs/mmpose/pose-detection_simcc_onnxruntime_static-384x288"$withFP16".py \
     /mmpose/projects/rtmpose/rtmpose/wholebody_2d_keypoint/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py \
-    https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-coco-wholebody_pt-aic-coco_270e-384x288-eaeb96c8_20230125.pth \
+    https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-ucoco_dw-ucoco_270e-384x288-2438fd99_20230728.pth \
     /mmpose/projects/rtmpose/examples/onnxruntime/human-pose.jpeg \
     --work-dir work_dir \
     --show
@@ -70,7 +70,7 @@ mv /mmdeploy/work_dir/end2end.onnx /RapidPoseTriangulation/extras/mmdeploy/expor
 python3 ./tools/deploy.py \
     configs/mmpose/pose-detection_simcc_onnxruntime_dynamic-384x288"$withFP16".py \
     /mmpose/projects/rtmpose/rtmpose/wholebody_2d_keypoint/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py \
-    https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-coco-wholebody_pt-aic-coco_270e-384x288-eaeb96c8_20230125.pth \
+    https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-ucoco_dw-ucoco_270e-384x288-2438fd99_20230728.pth \
     /mmpose/projects/rtmpose/examples/onnxruntime/human-pose.jpeg \
     --work-dir work_dir \
     --show
diff --git a/extras/mmpose/README.md b/extras/mmpose/README.md
new file mode 100644
index 0000000..c731136
--- /dev/null
+++ b/extras/mmpose/README.md
@@ -0,0 +1,23 @@
+# Finetuning MMPose models
+
+See: <https://mmpose.readthedocs.io/en/latest/user_guides/train_and_test.html>
+
+<br>
+
+```bash
+docker build --progress=plain -f extras/mmpose/dockerfile -t rpt_mmpose .
+
+./extras/mmpose/run_container.sh
+```
+
+```bash
+cd /mmpose/
+export CUDA_VISIBLE_DEVICES=0
+
+python3 ./tools/train.py \
+    /RapidPoseTriangulation/extras/mmpose/configs/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py \
+    --amp \
+    --cfg-options \
+      load_from=https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-coco-wholebody_pt-aic-coco_270e-384x288-eaeb96c8_20230125.pth \
+      base_lr=0.00004
+```
diff --git a/extras/mmpose/configs/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py b/extras/mmpose/configs/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py
new file mode 100644
index 0000000..9af4ae2
--- /dev/null
+++ b/extras/mmpose/configs/rtmpose-l_8xb32-270e_coco-wholebody-384x288.py
@@ -0,0 +1,235 @@
+_base_ = ['mmpose::_base_/default_runtime.py']
+
+val_interval=1
+max_epochs = 3
+
+# common setting
+num_keypoints = 133
+input_size = (288, 384)
+
+# runtime
+stage2_num_epochs = 30
+base_lr = 4e-3
+train_batch_size = 32
+val_batch_size = 32
+
+train_cfg = dict(max_epochs=max_epochs, val_interval=val_interval)
+randomness = dict(seed=21)
+
+# optimizer
+optim_wrapper = dict(
+    type='OptimWrapper',
+    optimizer=dict(type='AdamW', lr=base_lr, weight_decay=0.05),
+    clip_grad=dict(max_norm=35, norm_type=2),
+    paramwise_cfg=dict(
+        norm_decay_mult=0, bias_decay_mult=0, bypass_duplicate=True))
+
+# learning rate
+param_scheduler = [
+    dict(
+        type='LinearLR',
+        start_factor=1.0e-5,
+        by_epoch=False,
+        begin=0,
+        end=1000),
+    dict(
+        type='CosineAnnealingLR',
+        eta_min=base_lr * 0.05,
+        begin=max_epochs // 2,
+        end=max_epochs,
+        T_max=max_epochs // 2,
+        by_epoch=True,
+        convert_to_iter_based=True),
+]
+
+# automatically scaling LR based on the actual training batch size
+auto_scale_lr = dict(base_batch_size=512)
+
+# codec settings
+codec = dict(
+    type='SimCCLabel',
+    input_size=input_size,
+    sigma=(6., 6.93),
+    simcc_split_ratio=2.0,
+    normalize=False,
+    use_dark=False)
+
+# model settings
+model = dict(
+    type='TopdownPoseEstimator',
+    data_preprocessor=dict(
+        type='PoseDataPreprocessor',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        bgr_to_rgb=True),
+    backbone=dict(
+        _scope_='mmdet',
+        type='CSPNeXt',
+        arch='P5',
+        expand_ratio=0.5,
+        deepen_factor=1.,
+        widen_factor=1.,
+        out_indices=(4, ),
+        channel_attention=True,
+        norm_cfg=dict(type='SyncBN'),
+        act_cfg=dict(type='SiLU'),
+        init_cfg=dict(
+            type='Pretrained',
+            prefix='backbone.',
+            checkpoint='https://download.openmmlab.com/mmpose/v1/projects/'
+            'rtmposev1/cspnext-l_udp-aic-coco_210e-256x192-273b7631_20230130.pth'  # noqa
+        )),
+    head=dict(
+        type='RTMCCHead',
+        in_channels=1024,
+        out_channels=num_keypoints,
+        input_size=codec['input_size'],
+        in_featuremap_size=tuple([s // 32 for s in codec['input_size']]),
+        simcc_split_ratio=codec['simcc_split_ratio'],
+        final_layer_kernel_size=7,
+        gau_cfg=dict(
+            hidden_dims=256,
+            s=128,
+            expansion_factor=2,
+            dropout_rate=0.,
+            drop_path=0.,
+            act_fn='SiLU',
+            use_rel_bias=False,
+            pos_enc=False),
+        loss=dict(
+            type='KLDiscretLoss',
+            use_target_weight=True,
+            beta=10.,
+            label_softmax=True),
+        decoder=codec),
+    test_cfg=dict(flip_test=True, ))
+
+# base dataset settings
+dataset_type = 'CocoWholeBodyDataset'
+data_mode = 'topdown'
+data_root = 'data/coco/'
+
+backend_args = dict(backend='local')
+
+# pipelines
+train_pipeline = [
+    dict(type='LoadImage', backend_args=backend_args),
+    dict(type='GetBBoxCenterScale'),
+    dict(type='RandomFlip', direction='horizontal'),
+    dict(type='RandomHalfBody'),
+    dict(
+        type='RandomBBoxTransform', scale_factor=[0.6, 1.4], rotate_factor=80),
+    dict(type='TopdownAffine', input_size=codec['input_size']),
+    dict(type='mmdet.YOLOXHSVRandomAug'),
+    dict(
+        type='Albumentation',
+        transforms=[
+            dict(type='Blur', p=0.1),
+            dict(type='MedianBlur', p=0.1),
+            dict(
+                type='CoarseDropout',
+                max_holes=1,
+                max_height=0.4,
+                max_width=0.4,
+                min_holes=1,
+                min_height=0.2,
+                min_width=0.2,
+                p=1.0),
+        ]),
+    dict(type='GenerateTarget', encoder=codec),
+    dict(type='PackPoseInputs')
+]
+val_pipeline = [
+    dict(type='LoadImage', backend_args=backend_args),
+    dict(type='GetBBoxCenterScale'),
+    dict(type='TopdownAffine', input_size=codec['input_size']),
+    dict(type='PackPoseInputs')
+]
+
+train_pipeline_stage2 = [
+    dict(type='LoadImage', backend_args=backend_args),
+    dict(type='GetBBoxCenterScale'),
+    dict(type='RandomFlip', direction='horizontal'),
+    dict(type='RandomHalfBody'),
+    dict(
+        type='RandomBBoxTransform',
+        shift_factor=0.,
+        scale_factor=[0.75, 1.25],
+        rotate_factor=60),
+    dict(type='TopdownAffine', input_size=codec['input_size']),
+    dict(type='mmdet.YOLOXHSVRandomAug'),
+    dict(
+        type='Albumentation',
+        transforms=[
+            dict(type='Blur', p=0.1),
+            dict(type='MedianBlur', p=0.1),
+            dict(
+                type='CoarseDropout',
+                max_holes=1,
+                max_height=0.4,
+                max_width=0.4,
+                min_holes=1,
+                min_height=0.2,
+                min_width=0.2,
+                p=0.5),
+        ]),
+    dict(type='GenerateTarget', encoder=codec),
+    dict(type='PackPoseInputs')
+]
+
+# data loaders
+train_dataloader = dict(
+    batch_size=train_batch_size,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(type='DefaultSampler', shuffle=True),
+    dataset=dict(
+        type=dataset_type,
+        data_root=data_root,
+        data_mode=data_mode,
+        ann_file='annotations/coco_wholebody_train_v1.0.json',
+        data_prefix=dict(img='train2017/'),
+        pipeline=train_pipeline,
+    ))
+val_dataloader = dict(
+    batch_size=val_batch_size,
+    num_workers=10,
+    persistent_workers=True,
+    drop_last=False,
+    sampler=dict(type='DefaultSampler', shuffle=False, round_up=False),
+    dataset=dict(
+        type=dataset_type,
+        data_root=data_root,
+        data_mode=data_mode,
+        ann_file='annotations/coco_wholebody_val_v1.0.json',
+        data_prefix=dict(img='val2017/'),
+        test_mode=True,
+        # bbox_file='data/coco/person_detection_results/'
+        # 'COCO_val2017_detections_AP_H_56_person.json',
+        pipeline=val_pipeline,
+    ))
+test_dataloader = val_dataloader
+
+# hooks
+default_hooks = dict(
+    checkpoint=dict(
+        save_best='coco-wholebody/AP', rule='greater', max_keep_ckpts=1))
+
+custom_hooks = [
+    dict(
+        type='EMAHook',
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        update_buffers=True,
+        priority=49),
+    dict(
+        type='mmdet.PipelineSwitchHook',
+        switch_epoch=max_epochs - stage2_num_epochs,
+        switch_pipeline=train_pipeline_stage2)
+]
+
+# evaluators
+val_evaluator = dict(
+    type='CocoWholeBodyMetric',
+    ann_file=data_root + 'annotations/coco_wholebody_val_v1.0.json')
+test_evaluator = val_evaluator
diff --git a/extras/mmpose/dockerfile b/extras/mmpose/dockerfile
new file mode 100644
index 0000000..455ba87
--- /dev/null
+++ b/extras/mmpose/dockerfile
@@ -0,0 +1,9 @@
+FROM rpt_mmdeploy
+
+RUN apt-get update && apt-get install -y --no-install-recommends nano
+RUN pip3 install --upgrade --no-cache-dir "albumentations<1.4"
+
+RUN sed -i '94i\        self.runner.val_loop.run()' /usr/local/lib/python3.8/dist-packages/mmengine/runner/loops.py
+
+WORKDIR /mmpose/
+CMD ["/bin/bash"]
diff --git a/extras/mmpose/run_container.sh b/extras/mmpose/run_container.sh
new file mode 100755
index 0000000..2b0ed92
--- /dev/null
+++ b/extras/mmpose/run_container.sh
@@ -0,0 +1,11 @@
+#! /bin/bash
+
+xhost +
+docker run --privileged --rm --network host -it \
+  --gpus all --shm-size=16g --ulimit memlock=-1 --ulimit stack=67108864 \
+  --volume "$(pwd)"/:/RapidPoseTriangulation/ \
+  --volume "$(pwd)"/../datasets/coco2017/annotations/:/mmpose/data/coco/annotations/ \
+  --volume "$(pwd)"/../datasets/coco2017/images/:/mmpose/data/coco/ \
+  --volume /tmp/.X11-unix:/tmp/.X11-unix \
+  --env DISPLAY --env QT_X11_NO_MITSHM=1 \
+  rpt_mmpose
diff --git a/extras/ros/README.md b/extras/ros/README.md
index dda355f..757fbdd 100644
--- a/extras/ros/README.md
+++ b/extras/ros/README.md
@@ -7,10 +7,11 @@ Run pose estimator with ros topics as inputs and publish detected poses.
 - Build container:
 
   ```bash
-  docker build --progress=plain -t rapidposetriangulation_ros -f extras/ros/dockerfile .
+  docker build --progress=plain -t rapidposetriangulation_ros2d -f extras/ros/dockerfile_2d .
+  docker build --progress=plain -t rapidposetriangulation_ros3d -f extras/ros/dockerfile_3d .
   ```
 
-- Update or remove the `ROS_DOMAIN_ID` in `docker-compose.yml` to fit your environment
+- Update or remove the `ROS_DOMAIN_ID` in the `docker-compose.yml` files to fit your environment
 
 - Run and test:
 
diff --git a/extras/ros/docker-compose-2d.yml b/extras/ros/docker-compose-2d.yml
index 2501950..ba79b9f 100644
--- a/extras/ros/docker-compose-2d.yml
+++ b/extras/ros/docker-compose-2d.yml
@@ -1,10 +1,7 @@
-version: "2.3"
-# runtime: nvidia needs version 2 else change standard runtime at host pc
-
 services:
 
     test_node:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
@@ -15,13 +12,14 @@ services:
             - /tmp/.X11-unix:/tmp/.X11-unix
             - /dev/shm:/dev/shm
         environment:
+            - CAMID
             - DISPLAY
             - QT_X11_NO_MITSHM=1
             - "PYTHONUNBUFFERED=1"
         command: /bin/bash -i -c 'sleep infinity'
 
     estimator:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
@@ -39,7 +37,7 @@ services:
         command: /bin/bash -i -c 'export ROS_DOMAIN_ID=18 && ros2 run rpt2d_wrapper_cpp rpt2d_wrapper'
 
     pose_visualizer:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
@@ -57,7 +55,7 @@ services:
         command: /bin/bash -i -c 'sleep 2 && export ROS_DOMAIN_ID=18 && ros2 run pose2d_visualizer pose2d_visualizer $CAMID'
 
     pose_viewer:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros2d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
diff --git a/extras/ros/docker-compose-3d.yml b/extras/ros/docker-compose-3d.yml
index f567b87..750168b 100644
--- a/extras/ros/docker-compose-3d.yml
+++ b/extras/ros/docker-compose-3d.yml
@@ -1,10 +1,7 @@
-version: "2.3"
-# runtime: nvidia needs version 2 else change standard runtime at host pc
-
 services:
 
     test_node:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros3d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
@@ -21,7 +18,7 @@ services:
         command: /bin/bash -i -c 'sleep infinity'
 
     triangulator:
-        image: rapidposetriangulation_ros
+        image: rapidposetriangulation_ros3d
         network_mode: "host"
         ipc: "host"
         runtime: nvidia
diff --git a/extras/ros/dockerfile b/extras/ros/dockerfile_2d
similarity index 94%
rename from extras/ros/dockerfile
rename to extras/ros/dockerfile_2d
index 3def5aa..fe72c48 100644
--- a/extras/ros/dockerfile
+++ b/extras/ros/dockerfile_2d
@@ -45,17 +45,14 @@ RUN echo "source /project/dev_ws/install/setup.bash" >> ~/.bashrc
 # Copy modules
 COPY ./extras/include/ /RapidPoseTriangulation/extras/include/
 COPY ./scripts/ /RapidPoseTriangulation/scripts/
-COPY ./rpt/ /RapidPoseTriangulation/rpt/
 COPY ./extras/ros/rpt_msgs/ /RapidPoseTriangulation/extras/ros/rpt_msgs/
 COPY ./extras/ros/pose2d_visualizer/ /RapidPoseTriangulation/extras/ros/pose2d_visualizer/
 COPY ./extras/ros/rpt2d_wrapper_cpp/ /RapidPoseTriangulation/extras/ros/rpt2d_wrapper_cpp/
-COPY ./extras/ros/rpt3d_wrapper_cpp/ /RapidPoseTriangulation/extras/ros/rpt3d_wrapper_cpp/
 
 # Link and build as ros package
 RUN ln -s /RapidPoseTriangulation/extras/ros/rpt_msgs/ /project/dev_ws/src/
 RUN ln -s /RapidPoseTriangulation/extras/ros/pose2d_visualizer/ /project/dev_ws/src/
 RUN ln -s /RapidPoseTriangulation/extras/ros/rpt2d_wrapper_cpp/ /project/dev_ws/src/
-RUN ln -s /RapidPoseTriangulation/extras/ros/rpt3d_wrapper_cpp/ /project/dev_ws/src/
 RUN /bin/bash -i -c 'cd /project/dev_ws/; colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release'
 
 # Update ros packages -> autocompletion and check
diff --git a/extras/ros/dockerfile_3d b/extras/ros/dockerfile_3d
new file mode 100644
index 0000000..273d278
--- /dev/null
+++ b/extras/ros/dockerfile_3d
@@ -0,0 +1,44 @@
+FROM ros:humble-ros-base-jammy
+ARG DEBIAN_FRONTEND=noninteractive
+
+# Set the working directory to /project
+WORKDIR /project/
+
+# Update and install basic tools
+RUN apt-get update && apt-get upgrade -y
+RUN apt-get update && apt-get install -y --no-install-recommends git nano wget
+RUN apt-get update && apt-get install -y --no-install-recommends python3-pip
+RUN pip3 install --upgrade pip
+
+# Fix ros package building error
+RUN pip3 install --no-cache-dir "setuptools<=58.2.0"
+
+# Add ROS2 sourcing by default
+RUN echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc
+
+# Create ROS2 workspace for project packages
+RUN mkdir -p /project/dev_ws/src/
+RUN cd /project/dev_ws/; colcon build
+RUN echo "source /project/dev_ws/install/setup.bash" >> ~/.bashrc
+
+# Copy modules
+COPY ./extras/include/ /RapidPoseTriangulation/extras/include/
+COPY ./rpt/ /RapidPoseTriangulation/rpt/
+COPY ./extras/ros/rpt_msgs/ /RapidPoseTriangulation/extras/ros/rpt_msgs/
+COPY ./extras/ros/rpt3d_wrapper_cpp/ /RapidPoseTriangulation/extras/ros/rpt3d_wrapper_cpp/
+
+# Link and build as ros package
+RUN ln -s /RapidPoseTriangulation/extras/ros/rpt_msgs/ /project/dev_ws/src/
+RUN ln -s /RapidPoseTriangulation/extras/ros/rpt3d_wrapper_cpp/ /project/dev_ws/src/
+RUN /bin/bash -i -c 'cd /project/dev_ws/; colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release'
+
+# Update ros packages -> autocompletion and check
+RUN /bin/bash -i -c 'ros2 pkg list'
+
+# Clear cache to save space, only has an effect if image is squashed
+RUN apt-get autoremove -y \
+  && apt-get clean \
+  && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /RapidPoseTriangulation/
+CMD ["/bin/bash"]
diff --git a/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp b/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
index b7e7638..b6314e4 100644
--- a/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
+++ b/extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp
@@ -36,7 +36,7 @@ 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 = 0.95;
+static const float min_match_score = 0.92;
 static const size_t min_group_size = 1;
 
 static const std::array<std::array<float, 3>, 2> roomparams = {{
diff --git a/media/RESULTS.md b/media/RESULTS.md
index 8611354..5d50642 100644
--- a/media/RESULTS.md
+++ b/media/RESULTS.md
@@ -7,26 +7,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0209406,
-  "demosaicing": 0.00061778,
-  "avg_time_2d": 0.0081745,
-  "avg_time_3d": 3.67151e-05,
-  "fps": 113.263
+  "img_loading": 0.0209358,
+  "demosaicing": 0.000623902,
+  "avg_time_2d": 0.00826655,
+  "avg_time_3d": 3.62631e-05,
+  "fps": 112.023
 }
 {
   "triangulator_calls": 600,
-  "init_time": 2.64651e-06,
-  "undistort_time": 3.72878e-06,
-  "project_time": 7.91012e-07,
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 }
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   "total_parts": 8400,
-  "correct_parts": 8122,
-  "pcp": 0.966905
+  "correct_parts": 8133,
+  "pcp": 0.968214
 }
 ```
 
@@ -294,26 +294,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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+  "convert_time": 1.18299e-07,
+  "total_time": 0.000108228
 }
 {
   "person_nums": {
@@ -332,52 +332,52 @@ Results of the model in various experiments on different datasets. \
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@@ -386,12 +386,12 @@ Results of the model in various experiments on different datasets. \
   },
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@@ -402,14 +402,14 @@ Results of the model in various experiments on different datasets. \
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@@ -482,15 +482,15 @@ Results of the model in various experiments on different datasets. \
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@@ -498,14 +498,14 @@ Results of the model in various experiments on different datasets. \
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@@ -514,15 +514,15 @@ Results of the model in various experiments on different datasets. \
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@@ -530,14 +530,14 @@ Results of the model in various experiments on different datasets. \
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@@ -546,14 +546,14 @@ Results of the model in various experiments on different datasets. \
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@@ -562,18 +562,18 @@ Results of the model in various experiments on different datasets. \
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-  "correct_parts": 6619,
-  "pcp": 0.991165
+  "correct_parts": 6623,
+  "pcp": 0.991764
 }
 ```
 
@@ -581,26 +581,26 @@ Results of the model in various experiments on different datasets. \
 
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   "total_parts": 5264,
-  "correct_parts": 4939,
-  "pcp": 0.93826
+  "correct_parts": 5000,
+  "pcp": 0.949848
 }
 ```
 
@@ -868,222 +868,222 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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-  "avg_time_2d": 0.00810187,
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+  "avg_time_2d": 0.00811287,
+  "avg_time_3d": 4.96537e-05,
+  "fps": 118.432
 }
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+  "post_time": 6.82835e-06,
+  "convert_time": 1.10684e-07,
+  "total_time": 4.45239e-05
 }
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 }
 {
   "total_parts": 10610,
-  "correct_parts": 6187,
-  "pcp": 0.583129
+  "correct_parts": 6153,
+  "pcp": 0.579925
 }
 ```
 
@@ -1091,74 +1091,74 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.00104159,
-  "avg_time_2d": 0.0167446,
-  "avg_time_3d": 0.000146181,
-  "fps": 55.765
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+  "demosaicing": 0.00102805,
+  "avg_time_2d": 0.0167614,
+  "avg_time_3d": 0.000149111,
+  "fps": 55.7457
 }
 {
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+  "post_time": 8.66923e-06,
+  "convert_time": 1.53517e-07,
+  "total_time": 0.000139126
 }
 {
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+    "total_preds": 1499,
     "considered_empty": 0,
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@@ -1167,13 +1167,13 @@ Results of the model in various experiments on different datasets. \
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@@ -1183,14 +1183,14 @@ Results of the model in various experiments on different datasets. \
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@@ -1199,30 +1199,30 @@ Results of the model in various experiments on different datasets. \
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+  "correct_parts": 20236,
+  "pcp": 0.989826
 }
 ```
 
@@ -1378,286 +1378,286 @@ Results of the model in various experiments on different datasets. \
 
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-  "pcp": 0.895519
+  "correct_parts": 18292,
+  "pcp": 0.894737
 }
 ```
 
@@ -1665,26 +1665,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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 {
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@@ -1741,14 +1741,14 @@ Results of the model in various experiments on different datasets. \
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@@ -1757,14 +1757,14 @@ Results of the model in various experiments on different datasets. \
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@@ -1773,15 +1773,15 @@ Results of the model in various experiments on different datasets. \
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@@ -1789,31 +1789,31 @@ Results of the model in various experiments on different datasets. \
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@@ -1821,30 +1821,30 @@ Results of the model in various experiments on different datasets. \
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@@ -1853,31 +1853,31 @@ Results of the model in various experiments on different datasets. \
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@@ -1885,66 +1885,66 @@ Results of the model in various experiments on different datasets. \
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   "joint_recalls": {
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+    "recall-0.5": 0.99747
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 }
 {
   "total_parts": 20444,
-  "correct_parts": 20347,
-  "pcp": 0.995255
+  "correct_parts": 20356,
+  "pcp": 0.995696
 }
 ```
 
@@ -1952,74 +1952,74 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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-  "demosaicing": 0.011528,
-  "avg_time_2d": 0.0978827,
-  "avg_time_3d": 0.0051087,
-  "fps": 8.73215
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+  "demosaicing": 0.0120481,
+  "avg_time_2d": 0.0983697,
+  "avg_time_3d": 0.00517295,
+  "fps": 8.65121
 }
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-  "post_time": 9.92854e-06,
-  "convert_time": 2.1015e-07,
-  "total_time": 0.00493674
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+  "undistort_time": 9.94009e-05,
+  "project_time": 1.89077e-05,
+  "match_time": 8.2416e-05,
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+  "merge_time": 0.000705236,
+  "post_time": 1.11612e-05,
+  "convert_time": 1.97936e-07,
+  "total_time": 0.00499746
 }
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+    "total_preds": 1509,
     "considered_empty": 0,
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+    "invalid_preds": 44,
     "missing": 1,
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   "nose": {
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+    "mean": 0.009189,
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@@ -2028,13 +2028,13 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_left": {
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     "recall-0.15": 0.999318,
@@ -2044,12 +2044,12 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_right": {
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-    "std": 0.00704,
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@@ -2060,14 +2060,14 @@ Results of the model in various experiments on different datasets. \
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     "recall-0.25": 0.999317,
@@ -2076,14 +2076,14 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_right": {
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@@ -2092,14 +2092,14 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
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     "recall-0.25": 0.999303,
@@ -2108,15 +2108,15 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_right": {
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@@ -2124,13 +2124,13 @@ Results of the model in various experiments on different datasets. \
   },
   "hip_left": {
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     "recall-0.15": 0.999317,
@@ -2140,15 +2140,15 @@ Results of the model in various experiments on different datasets. \
   },
   "hip_right": {
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     "recall-0.25": 0.999318,
     "recall-0.5": 0.999318,
@@ -2156,15 +2156,15 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_left": {
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     "recall-0.5": 0.999317,
@@ -2172,66 +2172,66 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_right": {
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   "joint_recalls": {
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     "recall-0.25": 0.99879,
     "recall-0.5": 0.99889
   }
 }
 {
   "total_parts": 20444,
-  "correct_parts": 20406,
-  "pcp": 0.998141
+  "correct_parts": 20407,
+  "pcp": 0.99819
 }
 ```
 
@@ -2239,91 +2239,91 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
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-  "demosaicing": 0.000665234,
-  "avg_time_2d": 0.00859652,
-  "avg_time_3d": 3.16495e-05,
-  "fps": 107.603
+  "img_loading": 0.0317525,
+  "demosaicing": 0.000678883,
+  "avg_time_2d": 0.00854502,
+  "avg_time_3d": 3.28613e-05,
+  "fps": 108.029
 }
 {
   "triangulator_calls": 479,
-  "init_time": 2.97879e-06,
-  "undistort_time": 4.96341e-06,
-  "project_time": 4.24069e-07,
-  "match_time": 9.75025e-07,
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-  "post_time": 4.55531e-06,
-  "convert_time": 7.29624e-08,
-  "total_time": 2.78812e-05
+  "init_time": 2.81193e-06,
+  "undistort_time": 4.96263e-06,
+  "project_time": 4.2423e-07,
+  "match_time": 9.58927e-07,
+  "pairs_time": 3.71848e-07,
+  "pair_scoring_time": 7.13907e-06,
+  "grouping_time": 6.90313e-07,
+  "full_time": 3.95796e-06,
+  "merge_time": 2.12479e-06,
+  "post_time": 5.34428e-06,
+  "convert_time": 7.14739e-08,
+  "total_time": 2.90926e-05
 }
 {
   "person_nums": {
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     "total_labels": 479,
-    "total_preds": 597,
+    "total_preds": 584,
     "considered_empty": 0,
     "valid_preds": 443,
-    "invalid_preds": 154,
+    "invalid_preds": 141,
     "missing": 36,
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     "recall": 0.92484,
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+    "f1": 0.83349,
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   "mpjpe": {
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@@ -2346,30 +2346,30 @@ Results of the model in various experiments on different datasets. \
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+  "correct_parts": 3794,
+  "pcp": 0.879666
 }
 ```
 
@@ -2526,26 +2526,26 @@ Results of the model in various experiments on different datasets. \
 
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@@ -2618,95 +2618,95 @@ Results of the model in various experiments on different datasets. \
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@@ -2714,47 +2714,47 @@ Results of the model in various experiments on different datasets. \
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@@ -2762,14 +2762,14 @@ Results of the model in various experiments on different datasets. \
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@@ -2778,14 +2778,14 @@ Results of the model in various experiments on different datasets. \
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@@ -2794,18 +2794,18 @@ Results of the model in various experiments on different datasets. \
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 {
   "total_parts": 10920,
-  "correct_parts": 10718,
-  "pcp": 0.981502
+  "correct_parts": 10778,
+  "pcp": 0.986996
 }
 ```
 
@@ -2813,26 +2813,26 @@ Results of the model in various experiments on different datasets. \
 
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@@ -2851,37 +2851,37 @@ Results of the model in various experiments on different datasets. \
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@@ -2889,15 +2889,15 @@ Results of the model in various experiments on different datasets. \
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@@ -2905,15 +2905,15 @@ Results of the model in various experiments on different datasets. \
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@@ -2921,79 +2921,79 @@ Results of the model in various experiments on different datasets. \
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@@ -3001,15 +3001,15 @@ Results of the model in various experiments on different datasets. \
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@@ -3017,31 +3017,31 @@ Results of the model in various experiments on different datasets. \
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@@ -3049,14 +3049,14 @@ Results of the model in various experiments on different datasets. \
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     "recall-0.1": 0.951535,
     "recall-0.15": 0.959612,
     "recall-0.25": 0.966074,
@@ -3065,13 +3065,13 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_right": {
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-    "mean": 0.047183,
-    "median": 0.041684,
-    "std": 0.044559,
-    "sem": 0.001818,
-    "min": 0.005996,
-    "max": 0.453644,
-    "recall-0.025": 0.170418,
+    "mean": 0.047174,
+    "median": 0.041546,
+    "std": 0.044345,
+    "sem": 0.001809,
+    "min": 0.004139,
+    "max": 0.447056,
+    "recall-0.025": 0.173633,
     "recall-0.05": 0.694534,
     "recall-0.1": 0.940514,
     "recall-0.15": 0.951768,
@@ -3081,18 +3081,18 @@ Results of the model in various experiments on different datasets. \
   },
   "joint_recalls": {
     "num_labels": 8129,
-    "recall-0.025": 0.10764,
-    "recall-0.05": 0.58187,
-    "recall-0.1": 0.95707,
-    "recall-0.15": 0.98376,
+    "recall-0.025": 0.10936,
+    "recall-0.05": 0.59183,
+    "recall-0.1": 0.96039,
+    "recall-0.15": 0.98487,
     "recall-0.25": 0.98917,
     "recall-0.5": 0.99754
   }
 }
 {
   "total_parts": 8725,
-  "correct_parts": 8596,
-  "pcp": 0.985215
+  "correct_parts": 8613,
+  "pcp": 0.987163
 }
 ```
 
@@ -3102,26 +3102,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0237961,
-  "demosaicing": 0.000614795,
-  "avg_time_2d": 0.00829619,
-  "avg_time_3d": 3.31439e-05,
-  "fps": 111.805
+  "img_loading": 0.023819,
+  "demosaicing": 0.000592636,
+  "avg_time_2d": 0.00836484,
+  "avg_time_3d": 3.39228e-05,
+  "fps": 111.217
 }
 {
   "triangulator_calls": 200,
-  "init_time": 2.38789e-06,
-  "undistort_time": 3.87026e-06,
-  "project_time": 1.6185e-08,
-  "match_time": 1.6255e-08,
-  "pairs_time": 1.95465e-07,
-  "pair_scoring_time": 5.95505e-06,
-  "grouping_time": 9.36885e-07,
-  "full_time": 7.57055e-06,
-  "merge_time": 3.17569e-06,
-  "post_time": 4.01471e-06,
-  "convert_time": 5.971e-08,
-  "total_time": 2.84365e-05
+  "init_time": 2.32901e-06,
+  "undistort_time": 3.80476e-06,
+  "project_time": 1.5805e-08,
+  "match_time": 1.6475e-08,
+  "pairs_time": 1.94975e-07,
+  "pair_scoring_time": 5.96606e-06,
+  "grouping_time": 1.01088e-06,
+  "full_time": 7.36997e-06,
+  "merge_time": 3.18934e-06,
+  "post_time": 4.69211e-06,
+  "convert_time": 5.8275e-08,
+  "total_time": 2.88801e-05
 }
 {
   "person_nums": {
@@ -3140,12 +3140,12 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
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-    "median": 0.021578,
-    "std": 0.010126,
-    "sem": 0.000718,
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+    "median": 0.022282,
+    "std": 0.008704,
+    "sem": 0.000617,
+    "min": 0.010617,
+    "max": 0.07701,
     "recall-0.025": 0.67,
     "recall-0.05": 0.985,
     "recall-0.1": 1.0,
@@ -3153,8 +3153,8 @@ Results of the model in various experiments on different datasets. \
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 200,
-    "ap-0.025": 0.589809,
-    "ap-0.05": 0.984181,
+    "ap-0.025": 0.587964,
+    "ap-0.05": 0.984394,
     "ap-0.1": 1.0,
     "ap-0.15": 1.0,
     "ap-0.25": 1.0,
@@ -3162,30 +3162,30 @@ Results of the model in various experiments on different datasets. \
   },
   "nose": {
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-    "recall-0.1": 0.96,
-    "recall-0.15": 0.995,
+    "mean": 0.037471,
+    "median": 0.025849,
+    "std": 0.033736,
+    "sem": 0.002391,
+    "min": 0.003578,
+    "max": 0.182061,
+    "recall-0.025": 0.48,
+    "recall-0.05": 0.77,
+    "recall-0.1": 0.92,
+    "recall-0.15": 0.99,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 200
   },
   "shoulder_left": {
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-    "min": 0.00323,
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-    "recall-0.025": 0.82,
-    "recall-0.05": 0.98,
+    "mean": 0.019542,
+    "median": 0.016913,
+    "std": 0.011441,
+    "sem": 0.000811,
+    "min": 0.003239,
+    "max": 0.068476,
+    "recall-0.025": 0.75,
+    "recall-0.05": 0.97,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -3194,14 +3194,14 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_right": {
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-    "mean": 0.022008,
-    "median": 0.019454,
-    "std": 0.012077,
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-    "recall-0.05": 0.965,
+    "mean": 0.024473,
+    "median": 0.022001,
+    "std": 0.013062,
+    "sem": 0.000926,
+    "min": 0.003333,
+    "max": 0.089912,
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+    "recall-0.05": 0.945,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -3210,14 +3210,14 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_left": {
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-    "std": 0.012186,
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     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -3226,14 +3226,14 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_right": {
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+    "sem": 0.001318,
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     "recall-0.25": 1.0,
@@ -3242,62 +3242,62 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
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+    "sem": 0.002296,
+    "min": 0.000992,
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+    "recall-0.05": 0.935,
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-    "recall-0.25": 0.995,
+    "recall-0.15": 0.985,
+    "recall-0.25": 0.99,
     "recall-0.5": 1.0,
     "num_labels": 200
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   "wrist_right": {
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+    "median": 0.020619,
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+    "min": 0.001005,
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+    "recall-0.15": 0.995,
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   "hip_left": {
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+    "recall-0.05": 0.825,
     "recall-0.1": 0.995,
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+    "recall-0.15": 0.995,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 200
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   "hip_right": {
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     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -3306,82 +3306,82 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_left": {
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+    "max": 0.277156,
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-    "recall-0.15": 0.995,
+    "recall-0.05": 0.96,
+    "recall-0.1": 0.975,
+    "recall-0.15": 0.99,
     "recall-0.25": 0.995,
     "recall-0.5": 1.0,
     "num_labels": 200
   },
   "knee_right": {
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+    "recall-0.25": 1.0,
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     "num_labels": 200
   },
   "ankle_left": {
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   "ankle_right": {
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   "joint_recalls": {
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+    "recall-0.025": 0.67577,
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+    "recall-0.25": 0.99808,
+    "recall-0.5": 1.0
   }
 }
 {
   "total_parts": 2800,
-  "correct_parts": 2794,
-  "pcp": 0.997857
+  "correct_parts": 2796,
+  "pcp": 0.998571
 }
 ```
 
@@ -3389,26 +3389,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.0234424,
-  "demosaicing": 0.000597094,
-  "avg_time_2d": 0.0198536,
-  "avg_time_3d": 0.000112059,
-  "fps": 48.6316
+  "img_loading": 0.0235073,
+  "demosaicing": 0.000589444,
+  "avg_time_2d": 0.0116123,
+  "avg_time_3d": 0.000121054,
+  "fps": 81.1505
 }
 {
   "triangulator_calls": 200,
-  "init_time": 2.70115e-06,
-  "undistort_time": 2.53665e-05,
-  "project_time": 1.6065e-08,
-  "match_time": 1.628e-08,
-  "pairs_time": 1.9413e-07,
-  "pair_scoring_time": 5.7196e-06,
-  "grouping_time": 1.00915e-06,
-  "full_time": 4.30448e-05,
-  "merge_time": 1.30653e-05,
-  "post_time": 1.55649e-05,
-  "convert_time": 5.80455e-07,
-  "total_time": 0.000107512
+  "init_time": 2.67115e-06,
+  "undistort_time": 2.52513e-05,
+  "project_time": 1.555e-08,
+  "match_time": 1.642e-08,
+  "pairs_time": 1.9683e-07,
+  "pair_scoring_time": 5.97079e-06,
+  "grouping_time": 9.66385e-07,
+  "full_time": 4.41648e-05,
+  "merge_time": 1.4283e-05,
+  "post_time": 2.2505e-05,
+  "convert_time": 2.6854e-07,
+  "total_time": 0.000116544
 }
 {
   "person_nums": {
@@ -3427,21 +3427,21 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 200,
-    "mean": 0.043132,
-    "median": 0.039387,
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+    "mean": 0.04567,
+    "median": 0.042488,
+    "std": 0.01579,
+    "sem": 0.001119,
+    "min": 0.02021,
+    "max": 0.097066,
+    "recall-0.025": 0.025,
+    "recall-0.05": 0.715,
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     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 200,
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-    "ap-0.05": 0.655422,
+    "ap-0.025": 0.01062,
+    "ap-0.05": 0.62701,
     "ap-0.1": 1.0,
     "ap-0.15": 1.0,
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@@ -3449,63 +3449,63 @@ Results of the model in various experiments on different datasets. \
   },
   "nose": {
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+    "recall-0.05": 0.665,
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     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 200
   },
   "eye_left": {
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   "eye_right": {
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     "recall-0.25": 1.0,
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@@ -4986,43 +5626,43 @@ Results of the model in various experiments on different datasets. \
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     "body": {
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+    "recall-0.25": 0.9936,
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   }
 }
 {
@@ -5038,286 +5678,286 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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+  "demosaicing": 0.0117012,
+  "avg_time_2d": 0.0277632,
+  "avg_time_3d": 0.000309155,
+  "fps": 25.1424
 }
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+  "post_time": 1.10696e-05,
+  "convert_time": 2.1836e-07,
+  "total_time": 0.000298821
 }
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+    "recall-0.25": 0.94981,
+    "recall-0.5": 0.96173
   }
 }
 {
   "total_parts": 5600,
-  "correct_parts": 5277,
-  "pcp": 0.942321
+  "correct_parts": 5299,
+  "pcp": 0.94625
 }
 ```
 
@@ -5325,26 +5965,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.280666,
-  "demosaicing": 0.0112621,
-  "avg_time_2d": 0.023852,
-  "avg_time_3d": 0.000235742,
-  "fps": 28.2886
+  "img_loading": 0.28805,
+  "demosaicing": 0.0116658,
+  "avg_time_2d": 0.0242561,
+  "avg_time_3d": 0.000238594,
+  "fps": 27.6545
 }
 {
   "triangulator_calls": 121,
-  "init_time": 3.87942e-06,
-  "undistort_time": 1.88965e-05,
-  "project_time": 3.84835e-06,
-  "match_time": 1.2984e-05,
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-  "post_time": 7.14949e-06,
-  "convert_time": 1.34868e-07,
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+  "undistort_time": 1.86801e-05,
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@@ -5401,30 +6041,30 @@ Results of the model in various experiments on different datasets. \
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@@ -5433,14 +6073,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5465,14 +6105,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5529,15 +6169,15 @@ Results of the model in various experiments on different datasets. \
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@@ -5545,14 +6185,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5561,43 +6201,43 @@ Results of the model in various experiments on different datasets. \
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@@ -5612,26 +6252,26 @@ Results of the model in various experiments on different datasets. \
 
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 }
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@@ -5650,36 +6290,36 @@ Results of the model in various experiments on different datasets. \
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@@ -5688,14 +6328,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5704,30 +6344,30 @@ Results of the model in various experiments on different datasets. \
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@@ -5736,13 +6376,13 @@ Results of the model in various experiments on different datasets. \
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@@ -5752,15 +6392,15 @@ Results of the model in various experiments on different datasets. \
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@@ -5768,15 +6408,15 @@ Results of the model in various experiments on different datasets. \
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@@ -5784,14 +6424,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5800,14 +6440,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5816,14 +6456,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5832,15 +6472,15 @@ Results of the model in various experiments on different datasets. \
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@@ -5848,14 +6488,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5864,14 +6504,14 @@ Results of the model in various experiments on different datasets. \
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@@ -5880,10 +6520,10 @@ Results of the model in various experiments on different datasets. \
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@@ -5899,75 +6539,75 @@ Results of the model in various experiments on different datasets. \
 
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@@ -5975,14 +6615,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6087,14 +6727,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6103,15 +6743,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6119,14 +6759,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6135,15 +6775,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6151,15 +6791,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6167,9 +6807,9 @@ Results of the model in various experiments on different datasets. \
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@@ -6177,8 +6817,8 @@ Results of the model in various experiments on different datasets. \
 }
 {
   "total_parts": 4620,
-  "correct_parts": 4602,
-  "pcp": 0.996104
+  "correct_parts": 4604,
+  "pcp": 0.996537
 }
 ```
 
@@ -6186,26 +6826,26 @@ Results of the model in various experiments on different datasets. \
 
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 }
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@@ -6224,52 +6864,52 @@ Results of the model in various experiments on different datasets. \
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@@ -6278,15 +6918,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6294,15 +6934,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6310,62 +6950,62 @@ Results of the model in various experiments on different datasets. \
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@@ -6374,15 +7014,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6390,15 +7030,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6406,14 +7046,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6422,13 +7062,13 @@ Results of the model in various experiments on different datasets. \
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@@ -6438,14 +7078,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6454,11 +7094,11 @@ Results of the model in various experiments on different datasets. \
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   }
 }
@@ -6473,59 +7113,59 @@ Results of the model in various experiments on different datasets. \
 
 ```json
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 }
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+  "convert_time": 2.03694e-07,
+  "total_time": 0.000721604
 }
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@@ -6533,31 +7173,31 @@ Results of the model in various experiments on different datasets. \
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@@ -6565,14 +7205,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6581,15 +7221,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6597,15 +7237,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6613,15 +7253,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6629,30 +7269,30 @@ Results of the model in various experiments on different datasets. \
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@@ -6661,14 +7301,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6677,14 +7317,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6693,14 +7333,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6709,14 +7349,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6725,15 +7365,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6741,18 +7381,18 @@ Results of the model in various experiments on different datasets. \
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 }
 {
   "total_parts": 10248,
-  "correct_parts": 10240,
-  "pcp": 0.999219
+  "correct_parts": 10242,
+  "pcp": 0.999415
 }
 ```
 
@@ -6760,26 +7400,26 @@ Results of the model in various experiments on different datasets. \
 
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 {
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@@ -6798,50 +7438,50 @@ Results of the model in various experiments on different datasets. \
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@@ -6852,15 +7492,15 @@ Results of the model in various experiments on different datasets. \
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@@ -6868,30 +7508,30 @@ Results of the model in various experiments on different datasets. \
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@@ -6900,14 +7540,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6916,14 +7556,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6932,12 +7572,12 @@ Results of the model in various experiments on different datasets. \
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@@ -6948,14 +7588,14 @@ Results of the model in various experiments on different datasets. \
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@@ -6964,12 +7604,12 @@ Results of the model in various experiments on different datasets. \
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@@ -6980,13 +7620,13 @@ Results of the model in various experiments on different datasets. \
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@@ -6996,14 +7636,14 @@ Results of the model in various experiments on different datasets. \
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@@ -7012,14 +7652,14 @@ Results of the model in various experiments on different datasets. \
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     "count": 362,
-    "mean": 0.018893,
-    "median": 0.014002,
-    "std": 0.028283,
-    "sem": 0.001489,
-    "min": 0.000791,
-    "max": 0.49458,
-    "recall-0.025": 0.825967,
-    "recall-0.05": 0.966851,
+    "mean": 0.018432,
+    "median": 0.013868,
+    "std": 0.028382,
+    "sem": 0.001494,
+    "min": 0.001421,
+    "max": 0.496813,
+    "recall-0.025": 0.837017,
+    "recall-0.05": 0.972376,
     "recall-0.1": 0.994475,
     "recall-0.15": 0.997238,
     "recall-0.25": 0.997238,
@@ -7028,17 +7668,17 @@ Results of the model in various experiments on different datasets. \
   },
   "joint_recalls": {
     "num_labels": 4706,
-    "recall-0.025": 0.65746,
-    "recall-0.05": 0.94794,
-    "recall-0.1": 0.99575,
-    "recall-0.15": 0.99873,
+    "recall-0.025": 0.66617,
+    "recall-0.05": 0.95155,
+    "recall-0.1": 0.9949,
+    "recall-0.15": 0.9983,
     "recall-0.25": 0.99894,
     "recall-0.5": 1.0
   }
 }
 {
   "total_parts": 5068,
-  "correct_parts": 5064,
-  "pcp": 0.999211
+  "correct_parts": 5061,
+  "pcp": 0.998619
 }
 ```
diff --git a/rpt/triangulator.cpp b/rpt/triangulator.cpp
index 1d9b049..005bcb1 100644
--- a/rpt/triangulator.cpp
+++ b/rpt/triangulator.cpp
@@ -525,6 +525,7 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
     }
 
     // Convert inputs to internal formats
+    this->num_cams = cameras.size();
     std::vector<std::vector<std::vector<std::array<float, 3>>>> i_poses_2d = poses_2d;
     std::vector<CameraInternal> internal_cameras;
     for (size_t i = 0; i < cameras.size(); ++i)
@@ -781,10 +782,6 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
         all_scored_poses[i] = std::move(std::make_pair(pose3d, score));
     }
 
-    elapsed = std::chrono::steady_clock::now() - stime;
-    pair_scoring_time += elapsed.count();
-    stime = std::chrono::steady_clock::now();
-
     // Drop low scoring poses
     size_t num_poses = all_scored_poses.size();
     for (size_t i = num_poses; i > 0; --i)
@@ -796,6 +793,10 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
         }
     }
 
+    elapsed = std::chrono::steady_clock::now() - stime;
+    pair_scoring_time += elapsed.count();
+    stime = std::chrono::steady_clock::now();
+
     // Group pairs that share a person
     std::vector<std::tuple<
         std::array<float, 3>, std::vector<std::array<float, 4>>, std::vector<int>>>
@@ -828,6 +829,27 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
 
         auto [pose3d, score] = triangulate_and_score(
             pose1, pose2, cam1, cam2, roomparams, {});
+
+        // Scale scores with 2D confidences
+        // They can improve the merge weighting, but especially the earlier step of pair-filtering
+        // works better if only per-view consistency is used, so they are not included before.
+        for (size_t j = 0; j < pose3d.size(); ++j)
+        {
+            float score1 = pose1[j][2];
+            float score2 = pose2[j][2];
+            float min_score = 0.1;
+
+            if (score1 > min_score && score2 > min_score)
+            {
+                float scoreP = (score1 + score2) * 0.5;
+                float scoreT = pose3d[j][3];
+
+                // Since the triangulation score is less sensitive and generally higher,
+                // weight it stronger to balance the two scores.
+                pose3d[j][3] = 0.9 * scoreT + 0.1 * scoreP;
+            }
+        }
+
         all_full_poses[i] = std::move(pose3d);
     }
 
@@ -862,6 +884,7 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
     add_extra_joints(final_poses_3d, joint_names);
     filter_poses(final_poses_3d, roomparams, core_joint_idx, core_limbs_idx);
     add_missing_joints(final_poses_3d, joint_names);
+    replace_far_joints(final_poses_3d, joint_names);
 
     // Store final result for use in the next frame.
     last_poses_3d = final_poses_3d;
@@ -1429,8 +1452,8 @@ std::pair<std::vector<std::array<float, 4>>, float> TriangulatorInternal::triang
     {
         if (mask[i])
         {
-            float score = 0.5 * (score1[i] + score2[i]);
-            pose3d[i][3] = score;
+            float scoreT = 0.5 * (score1[i] + score2[i]);
+            pose3d[i][3] = scoreT;
         }
     }
 
@@ -1787,7 +1810,8 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
     // Merge poses to create initial pose
     // Use only those triangulations with a high score
     std::vector<std::array<float, 4>> sum_poses(num_joints, {0.0, 0.0, 0.0, 0.0});
-    std::vector<int> sum_mask1(num_joints, 0);
+    std::vector<float> sum_mask1(num_joints, 0);
+    float offset1 = (1.0 - min_score) / 2.0;
     for (size_t i = 0; i < num_poses; ++i)
     {
         const auto &pose = poses_3d[i];
@@ -1795,13 +1819,14 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
         for (size_t j = 0; j < num_joints; ++j)
         {
             float score = pose[j][3];
-            if (score > min_score)
+            if (score > min_score - offset1)
             {
-                sum_poses[j][0] += pose[j][0];
-                sum_poses[j][1] += pose[j][1];
-                sum_poses[j][2] += pose[j][2];
-                sum_poses[j][3] += score;
-                sum_mask1[j]++;
+                float weight = std::pow(score, 2);
+                sum_poses[j][0] += pose[j][0] * weight;
+                sum_poses[j][1] += pose[j][1] * weight;
+                sum_poses[j][2] += pose[j][2] * weight;
+                sum_poses[j][3] += score * weight;
+                sum_mask1[j] += weight;
             }
         }
     }
@@ -1825,7 +1850,7 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
     for (size_t j = 0; j < num_joints; ++j)
     {
         float score = initial_pose_3d[j][3];
-        if (score > min_score)
+        if (score > min_score - offset1)
         {
             jmask[j] = true;
             center[0] += initial_pose_3d[j][0];
@@ -1853,7 +1878,7 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
     }
 
     // Drop joints with low scores and filter outlying joints using distance threshold
-    float offset = 0.1;
+    float offset2 = (1.0 - min_score) * 2.0;
     float max_dist_sq = 1.2 * 1.2;
     std::vector<std::vector<bool>> mask(num_poses, std::vector<bool>(num_joints, false));
     std::vector<std::vector<float>> distances(num_poses, std::vector<float>(num_joints, 0.0));
@@ -1869,7 +1894,7 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
             distances[i][j] = dist_sq;
 
             float score = pose[j][3];
-            if (dist_sq <= max_dist_sq && score > (min_score - offset))
+            if (dist_sq <= max_dist_sq && score > (min_score - offset2))
             {
                 mask[i][j] = true;
             }
@@ -1877,7 +1902,7 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
     }
 
     // Select the best-k proposals for each joint that are closest to the initial pose
-    int keep_best = std::max(3, (int)num_poses / 3);
+    int keep_best = std::max((int)std::ceil(this->num_cams / 2.0), (int)std::ceil(num_poses / 3.0));
     std::vector<std::vector<bool>> best_k_mask(num_poses, std::vector<bool>(num_joints, false));
     for (size_t j = 0; j < num_joints; ++j)
     {
@@ -1915,7 +1940,7 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
 
     // Compute the final pose
     std::vector<std::array<float, 4>> sum_poses2(num_joints, {0.0, 0.0, 0.0, 0.0});
-    std::vector<int> sum_mask2(num_joints, 0);
+    std::vector<float> sum_mask2(num_joints, 0);
     for (size_t i = 0; i < num_poses; ++i)
     {
         const auto &pose = poses_3d[i];
@@ -1924,11 +1949,13 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
         {
             if (mask[i][j])
             {
-                sum_poses2[j][0] += pose[j][0];
-                sum_poses2[j][1] += pose[j][1];
-                sum_poses2[j][2] += pose[j][2];
-                sum_poses2[j][3] += pose[j][3];
-                sum_mask2[j]++;
+                // Use an exponential weighting to give more importance to higher scores
+                float weight = std::pow(pose[j][3], 4);
+                sum_poses2[j][0] += pose[j][0] * weight;
+                sum_poses2[j][1] += pose[j][1] * weight;
+                sum_poses2[j][2] += pose[j][2] * weight;
+                sum_poses2[j][3] += pose[j][3] * weight;
+                sum_mask2[j] += weight;
             }
         }
     }
@@ -1993,15 +2020,17 @@ void TriangulatorInternal::filter_poses(
     for (size_t i = 0; i < poses.size(); ++i)
     {
         auto &pose = poses[i];
-        size_t num_joints = pose.size();
+        size_t num_core_joints = core_joint_idx.size();
+        size_t num_full_joints = pose.size();
 
         // Collect valid joint indices
         std::vector<size_t> valid_joint_idx;
-        for (size_t j = 0; j < num_joints; ++j)
+        for (size_t j = 0; j < num_core_joints; ++j)
         {
-            if (pose[j][3] > min_score)
+            size_t idx = core_joint_idx[j];
+            if (pose[idx][3] > min_score)
             {
-                valid_joint_idx.push_back(j);
+                valid_joint_idx.push_back(idx);
             }
         }
 
@@ -2099,6 +2128,23 @@ void TriangulatorInternal::filter_poses(
             continue;
         }
 
+        // Set joint scores outside the room to a low value
+        for (size_t j = 0; j < num_full_joints; ++j)
+        {
+            if (pose[j][3] > min_score)
+            {
+                for (int k = 0; k < 3; ++k)
+                {
+                    if (pose[j][k] > room_half_size[k] + room_center[k] + wdist ||
+                        pose[j][k] < -room_half_size[k] + room_center[k] - wdist)
+                    {
+                        pose[j][3] = 0.001;
+                        break;
+                    }
+                }
+            }
+        }
+
         // Calculate total limb length and average limb length
         const float max_avg_length = 0.5;
         const float min_avg_length = 0.1;
@@ -2179,132 +2225,104 @@ void TriangulatorInternal::add_missing_joints(
         {"wrist_right", {"elbow_right"}},
         {"wrist_left", {"elbow_left"}},
         {"nose", {"shoulder_middle", "shoulder_right", "shoulder_left"}},
-        {"head", {"shoulder_middle", "shoulder_right", "shoulder_left"}},
-        {"foot_*_left_*", {"ankle_left"}},
-        {"foot_*_right_*", {"ankle_right"}},
-        {"face_*", {"nose"}},
-        {"hand_*_left_*", {"wrist_left"}},
-        {"hand_*_right_*", {"wrist_right"}}};
+        {"head", {"shoulder_middle", "shoulder_right", "shoulder_left"}}};
+
+    // Collect adjacent joint mappings
+    std::vector<std::vector<size_t>> adjacent_indices;
+    adjacent_indices.resize(joint_names.size());
+    for (size_t j = 0; j < joint_names.size(); ++j)
+    {
+        std::string adname = "";
+        const std::string &jname = joint_names[j];
+
+        // Determine adjacent joint based on name patterns
+        if (adjacents.find(jname) != adjacents.end())
+        {
+            adname = jname;
+        }
+
+        if (!adname.empty())
+        {
+            auto it = adjacents.find(adname);
+            if (it != adjacents.end())
+            {
+                for (const std::string &adj_name : it->second)
+                {
+                    auto jt = joint_name_to_idx.find(adj_name);
+                    if (jt != joint_name_to_idx.end())
+                    {
+                        adjacent_indices[j].push_back(jt->second);
+                    }
+                }
+            }
+        }
+    }
 
     for (size_t i = 0; i < poses.size(); ++i)
     {
         auto &pose = poses[i];
         size_t num_joints = pose.size();
 
-        // Collect valid joint indices
-        std::vector<size_t> valid_joint_idx;
+        // Compute body center as the mean of valid joints
+        std::array<float, 3> body_center = {0.0, 0.0, 0.0};
+        size_t valid_count = 0;
         for (size_t j = 0; j < num_joints; ++j)
         {
             if (pose[j][3] > min_match_score)
             {
-                valid_joint_idx.push_back(j);
+                body_center[0] += pose[j][0];
+                body_center[1] += pose[j][1];
+                body_center[2] += pose[j][2];
+                valid_count++;
             }
         }
-
-        if (valid_joint_idx.empty())
+        if (valid_count == 0)
         {
             continue;
         }
-
-        // Compute body center as the mean of valid joints
-        std::array<float, 3> body_center = {0.0, 0.0, 0.0};
-        for (size_t idx : valid_joint_idx)
-        {
-            body_center[0] += pose[idx][0];
-            body_center[1] += pose[idx][1];
-            body_center[2] += pose[idx][2];
-        }
+        float inv_c = 1.0 / static_cast<float>(valid_count);
         for (int j = 0; j < 3; ++j)
         {
-            body_center[j] /= static_cast<float>(valid_joint_idx.size());
+            body_center[j] *= inv_c;
         }
 
         // Iterate over each joint
         for (size_t j = 0; j < joint_names.size(); ++j)
         {
-            std::string adname = "";
-            const std::string &jname = joint_names[j];
-
-            // Determine adjacent joint based on name patterns
-            if (jname.substr(0, 5) == "foot_" && jname.find("_left") != std::string::npos)
-            {
-                adname = "foot_*_left_*";
-            }
-            else if (jname.substr(0, 5) == "foot_" && jname.find("_right") != std::string::npos)
-            {
-                adname = "foot_*_right_*";
-            }
-            else if (jname.substr(0, 5) == "face_")
-            {
-                adname = "face_*";
-            }
-            else if (jname.substr(0, 5) == "hand_" && jname.find("_left") != std::string::npos)
-            {
-                adname = "hand_*_left_*";
-            }
-            else if (jname.substr(0, 5) == "hand_" && jname.find("_right") != std::string::npos)
-            {
-                adname = "hand_*_right_*";
-            }
-            else if (adjacents.find(jname) != adjacents.end())
-            {
-                adname = jname;
-            }
-
-            if (adname == "")
-            {
-                // No adjacent joints defined for this joint
-                continue;
-            }
-
             if (pose[j][3] == 0.0)
             {
-                if (adjacents.find(adname) != adjacents.end())
+                // Joint is missing; attempt to estimate its position based on adjacent joints
+                const std::vector<size_t> &adj_indices = adjacent_indices[j];
+                std::array<float, 3> adjacent_position = {0.0, 0.0, 0.0};
+                size_t adjacent_count = 0;
+
+                for (size_t adj_idx : adj_indices)
                 {
-                    // Joint is missing; attempt to estimate its position based on adjacent joints
-                    std::array<float, 3> adjacent_position = {0.0, 0.0, 0.0};
-                    size_t adjacent_count = 0;
-
-                    const std::vector<std::string> &adjacent_joint_names = adjacents[adname];
-                    for (const std::string &adj_name : adjacent_joint_names)
+                    if (adj_idx < pose.size() && pose[adj_idx][3] > 0.1)
                     {
-                        auto it = joint_name_to_idx.find(adj_name);
-                        if (it != joint_name_to_idx.end())
-                        {
-                            size_t adj_idx = it->second;
-                            if (adj_idx < pose.size() && pose[adj_idx][3] > 0.1)
-                            {
-                                adjacent_position[0] += pose[adj_idx][0];
-                                adjacent_position[1] += pose[adj_idx][1];
-                                adjacent_position[2] += pose[adj_idx][2];
-                                ++adjacent_count;
-                            }
-                        }
+                        adjacent_position[0] += pose[adj_idx][0];
+                        adjacent_position[1] += pose[adj_idx][1];
+                        adjacent_position[2] += pose[adj_idx][2];
+                        ++adjacent_count;
+                    }
+                }
+
+                if (adjacent_count > 0)
+                {
+                    float inv_c = 1.0 / static_cast<float>(adjacent_count);
+                    for (size_t k = 0; k < 3; ++k)
+                    {
+                        adjacent_position[k] *= inv_c;
                     }
 
-                    if (adjacent_count > 0)
-                    {
-                        for (size_t k = 0; k < 3; ++k)
-                        {
-                            adjacent_position[k] /= static_cast<float>(adjacent_count);
-                        }
-
-                        // Update the missing joint's position
-                        pose[j][0] = adjacent_position[0];
-                        pose[j][1] = adjacent_position[1];
-                        pose[j][2] = adjacent_position[2];
-                    }
-                    else
-                    {
-                        // No valid adjacent joints, use body center
-                        pose[j][0] = body_center[0];
-                        pose[j][1] = body_center[1];
-                        pose[j][2] = body_center[2];
-                    }
+                    // Update the missing joint's position
+                    pose[j][0] = adjacent_position[0];
+                    pose[j][1] = adjacent_position[1];
+                    pose[j][2] = adjacent_position[2];
                 }
                 else
                 {
-                    // Adjacent joints not defined, use body center
+                    // No valid adjacent joints, use body center
                     pose[j][0] = body_center[0];
                     pose[j][1] = body_center[1];
                     pose[j][2] = body_center[2];
@@ -2316,3 +2334,170 @@ void TriangulatorInternal::add_missing_joints(
         }
     }
 }
+
+// =================================================================================================
+
+void TriangulatorInternal::replace_far_joints(
+    std::vector<std::vector<std::array<float, 4>>> &poses,
+    const std::vector<std::string> &joint_names)
+{
+    for (size_t i = 0; i < poses.size(); ++i)
+    {
+        auto &pose = poses[i];
+        size_t num_full_joints = pose.size();
+
+        // Calculate the average position of pose parts
+        std::array<float, 4> center_head = {0.0, 0.0, 0.0, 0};
+        std::array<float, 4> center_foot_left = {0.0, 0.0, 0.0, 0};
+        std::array<float, 4> center_foot_right = {0.0, 0.0, 0.0, 0};
+        std::array<float, 4> center_hand_left = {0.0, 0.0, 0.0, 0};
+        std::array<float, 4> center_hand_right = {0.0, 0.0, 0.0, 0};
+        for (size_t j = 0; j < num_full_joints; ++j)
+        {
+            const std::string &jname = joint_names[j];
+            float offset2 = (1.0 - min_match_score) * 2;
+            float min_score = this->min_match_score - offset2;
+
+            if (pose[j][3] > min_score)
+            {
+                if (jname.compare(0, 4, "face_") == 0 || jname == "nose" || jname == "eye_left" ||
+                    jname == "eye_right" || jname == "ear_left" || jname == "ear_right")
+                {
+                    center_head[0] += pose[j][0];
+                    center_head[1] += pose[j][1];
+                    center_head[2] += pose[j][2];
+                    center_head[3] += 1.0;
+                }
+                else if (jname.compare(0, 5, "foot_") == 0 || jname.compare(0, 6, "ankle_") == 0)
+                {
+                    if (jname.find("_left") != std::string::npos)
+                    {
+                        center_foot_left[0] += pose[j][0];
+                        center_foot_left[1] += pose[j][1];
+                        center_foot_left[2] += pose[j][2];
+                        center_foot_left[3] += 1.0;
+                    }
+                    else if (jname.find("_right") != std::string::npos)
+                    {
+                        center_foot_right[0] += pose[j][0];
+                        center_foot_right[1] += pose[j][1];
+                        center_foot_right[2] += pose[j][2];
+                        center_foot_right[3] += 1.0;
+                    }
+                }
+                else if (jname.compare(0, 5, "hand_") == 0 || jname.compare(0, 6, "wrist_") == 0)
+                {
+                    if (jname.find("_left") != std::string::npos)
+                    {
+                        center_hand_left[0] += pose[j][0];
+                        center_hand_left[1] += pose[j][1];
+                        center_hand_left[2] += pose[j][2];
+                        center_hand_left[3] += 1.0;
+                    }
+                    else if (jname.find("_right") != std::string::npos)
+                    {
+                        center_hand_right[0] += pose[j][0];
+                        center_hand_right[1] += pose[j][1];
+                        center_hand_right[2] += pose[j][2];
+                        center_hand_right[3] += 1.0;
+                    }
+                }
+            }
+        }
+        for (size_t k = 0; k < 3; k++)
+        {
+            center_head[k] /= center_head[3];
+            center_foot_left[k] /= center_foot_left[3];
+            center_foot_right[k] /= center_foot_right[3];
+            center_hand_left[k] /= center_hand_left[3];
+            center_hand_right[k] /= center_hand_right[3];
+        }
+
+        // Drop joints that are too far from the part center
+        const float max_dist_head_sq = 0.20 * 0.20;
+        const float max_dist_foot_sq = 0.25 * 0.25;
+        const float max_dist_hand_sq = 0.20 * 0.20;
+        for (size_t j = 0; j < num_full_joints; ++j)
+        {
+            const std::string &jname = joint_names[j];
+
+            if (jname.compare(0, 4, "face_") == 0 || jname == "nose" || jname == "eye_left" ||
+                jname == "eye_right" || jname == "ear_left" || jname == "ear_right")
+            {
+                float dx = pose[j][0] - center_head[0];
+                float dy = pose[j][1] - center_head[1];
+                float dz = pose[j][2] - center_head[2];
+                float dist_sq = dx * dx + dy * dy + dz * dz;
+                if ((pose[j][3] > 0.0 && dist_sq > max_dist_head_sq) || pose[j][3] == 0.0)
+                {
+                    pose[j][0] = center_head[0];
+                    pose[j][1] = center_head[1];
+                    pose[j][2] = center_head[2];
+                    pose[j][3] = 0.1;
+                }
+            }
+            else if (jname.compare(0, 5, "foot_") == 0 || jname.compare(0, 6, "ankle_") == 0)
+            {
+                if (jname.find("_left") != std::string::npos)
+                {
+                    float dx = pose[j][0] - center_foot_left[0];
+                    float dy = pose[j][1] - center_foot_left[1];
+                    float dz = pose[j][2] - center_foot_left[2];
+                    float dist_sq = dx * dx + dy * dy + dz * dz;
+                    if ((pose[j][3] > 0.0 && dist_sq > max_dist_foot_sq) || pose[j][3] == 0.0)
+                    {
+                        pose[j][0] = center_foot_left[0];
+                        pose[j][1] = center_foot_left[1];
+                        pose[j][2] = center_foot_left[2];
+                        pose[j][3] = 0.1;
+                    }
+                }
+                else if (jname.find("_right") != std::string::npos)
+                {
+                    float dx = pose[j][0] - center_foot_right[0];
+                    float dy = pose[j][1] - center_foot_right[1];
+                    float dz = pose[j][2] - center_foot_right[2];
+                    float dist_sq = dx * dx + dy * dy + dz * dz;
+                    if ((pose[j][3] > 0.0 && dist_sq > max_dist_foot_sq) || pose[j][3] == 0.0)
+                    {
+                        pose[j][0] = center_foot_right[0];
+                        pose[j][1] = center_foot_right[1];
+                        pose[j][2] = center_foot_right[2];
+                        pose[j][3] = 0.1;
+                    }
+                }
+            }
+            else if (jname.compare(0, 5, "hand_") == 0 || jname.compare(0, 6, "wrist_") == 0)
+            {
+                if (jname.find("_left") != std::string::npos)
+                {
+                    float dx = pose[j][0] - center_hand_left[0];
+                    float dy = pose[j][1] - center_hand_left[1];
+                    float dz = pose[j][2] - center_hand_left[2];
+                    float dist_sq = dx * dx + dy * dy + dz * dz;
+                    if ((pose[j][3] > 0.0 && dist_sq > max_dist_hand_sq) || pose[j][3] == 0.0)
+                    {
+                        pose[j][0] = center_hand_left[0];
+                        pose[j][1] = center_hand_left[1];
+                        pose[j][2] = center_hand_left[2];
+                        pose[j][3] = 0.1;
+                    }
+                }
+                else if (jname.find("_right") != std::string::npos)
+                {
+                    float dx = pose[j][0] - center_hand_right[0];
+                    float dy = pose[j][1] - center_hand_right[1];
+                    float dz = pose[j][2] - center_hand_right[2];
+                    float dist_sq = dx * dx + dy * dy + dz * dz;
+                    if ((pose[j][3] > 0.0 && dist_sq > max_dist_hand_sq) || pose[j][3] == 0.0)
+                    {
+                        pose[j][0] = center_hand_right[0];
+                        pose[j][1] = center_hand_right[1];
+                        pose[j][2] = center_hand_right[2];
+                        pose[j][3] = 0.1;
+                    }
+                }
+            }
+        }
+    }
+}
diff --git a/rpt/triangulator.hpp b/rpt/triangulator.hpp
index 62c3615..36b724a 100644
--- a/rpt/triangulator.hpp
+++ b/rpt/triangulator.hpp
@@ -54,6 +54,7 @@ public:
 private:
     float min_match_score;
     float min_group_size;
+    size_t num_cams;
 
     const std::vector<std::string> core_joints = {
         "shoulder_left",
@@ -137,6 +138,10 @@ private:
         std::vector<std::vector<std::array<float, 4>>> &poses,
         const std::vector<std::string> &joint_names);
 
+    void replace_far_joints(
+        std::vector<std::vector<std::array<float, 4>>> &poses,
+        const std::vector<std::string> &joint_names);
+
     // Statistics
     double num_calls = 0;
     double total_time = 0;
diff --git a/scripts/utils_2d_pose.hpp b/scripts/utils_2d_pose.hpp
index 6be1d45..2fd98c5 100644
--- a/scripts/utils_2d_pose.hpp
+++ b/scripts/utils_2d_pose.hpp
@@ -1079,8 +1079,8 @@ namespace utils_2d_pose
 
             std::string path_pose_m1 = base_path + "rtmpose-m_1x384x288x3_fp16_extra-steps.onnx";
             std::string path_pose_mb = base_path + "rtmpose-m_Bx384x288x3_fp16_extra-steps.onnx";
-            std::string path_pose_w1 = base_path + "rtmpose-l_wb_1x384x288x3_extra-steps.onnx";
-            std::string path_pose_wb = base_path + "rtmpose-l_wb_Bx384x288x3_extra-steps.onnx";
+            std::string path_pose_w1 = base_path + "rtmpose-l_wb_1x384x288x3_fp16_extra-steps.onnx";
+            std::string path_pose_wb = base_path + "rtmpose-l_wb_Bx384x288x3_fp16_extra-steps.onnx";
 
             this->num_joints = whole_body ? 133 : 17;
             std::string path_det;
diff --git a/scripts/utils_pipeline.hpp b/scripts/utils_pipeline.hpp
index 436e041..8744c2a 100644
--- a/scripts/utils_pipeline.hpp
+++ b/scripts/utils_pipeline.hpp
@@ -139,47 +139,47 @@ namespace utils_pipeline
                 joint_names_2d.end(),
                 {
                     "hand_wrist_left",
-                    "finger_thumb_left_1",
-                    "finger_thumb_left_2",
-                    "finger_thumb_left_3",
-                    "finger_thumb_left_4",
-                    "finger_index_left_1",
-                    "finger_index_left_2",
-                    "finger_index_left_3",
-                    "finger_index_left_4",
-                    "finger_middle_left_1",
-                    "finger_middle_left_2",
-                    "finger_middle_left_3",
-                    "finger_middle_left_4",
-                    "finger_ring_left_1",
-                    "finger_ring_left_2",
-                    "finger_ring_left_3",
-                    "finger_ring_left_4",
-                    "finger_pinky_left_1",
-                    "finger_pinky_left_2",
-                    "finger_pinky_left_3",
-                    "finger_pinky_left_4",
+                    "hand_finger_thumb_left_1",
+                    "hand_finger_thumb_left_2",
+                    "hand_finger_thumb_left_3",
+                    "hand_finger_thumb_left_4",
+                    "hand_finger_index_left_1",
+                    "hand_finger_index_left_2",
+                    "hand_finger_index_left_3",
+                    "hand_finger_index_left_4",
+                    "hand_finger_middle_left_1",
+                    "hand_finger_middle_left_2",
+                    "hand_finger_middle_left_3",
+                    "hand_finger_middle_left_4",
+                    "hand_finger_ring_left_1",
+                    "hand_finger_ring_left_2",
+                    "hand_finger_ring_left_3",
+                    "hand_finger_ring_left_4",
+                    "hand_finger_pinky_left_1",
+                    "hand_finger_pinky_left_2",
+                    "hand_finger_pinky_left_3",
+                    "hand_finger_pinky_left_4",
                     "hand_wrist_right",
-                    "finger_thumb_right_1",
-                    "finger_thumb_right_2",
-                    "finger_thumb_right_3",
-                    "finger_thumb_right_4",
-                    "finger_index_right_1",
-                    "finger_index_right_2",
-                    "finger_index_right_3",
-                    "finger_index_right_4",
-                    "finger_middle_right_1",
-                    "finger_middle_right_2",
-                    "finger_middle_right_3",
-                    "finger_middle_right_4",
-                    "finger_ring_right_1",
-                    "finger_ring_right_2",
-                    "finger_ring_right_3",
-                    "finger_ring_right_4",
-                    "finger_pinky_right_1",
-                    "finger_pinky_right_2",
-                    "finger_pinky_right_3",
-                    "finger_pinky_right_4",
+                    "hand_finger_thumb_right_1",
+                    "hand_finger_thumb_right_2",
+                    "hand_finger_thumb_right_3",
+                    "hand_finger_thumb_right_4",
+                    "hand_finger_index_right_1",
+                    "hand_finger_index_right_2",
+                    "hand_finger_index_right_3",
+                    "hand_finger_index_right_4",
+                    "hand_finger_middle_right_1",
+                    "hand_finger_middle_right_2",
+                    "hand_finger_middle_right_3",
+                    "hand_finger_middle_right_4",
+                    "hand_finger_ring_right_1",
+                    "hand_finger_ring_right_2",
+                    "hand_finger_ring_right_3",
+                    "hand_finger_ring_right_4",
+                    "hand_finger_pinky_right_1",
+                    "hand_finger_pinky_right_2",
+                    "hand_finger_pinky_right_3",
+                    "hand_finger_pinky_right_4",
                 });
         }