From e9eb4c5d96aa7c239aad11aa4bf2888d42e96a8c Mon Sep 17 00:00:00 2001
From: Daniel <daniel@mail.de>
Date: Mon, 10 Mar 2025 11:48:51 +0100
Subject: [PATCH] Weigh positions at merge by exponential score.

---
 media/RESULTS.md     | 1154 +++++++++++++++++++++---------------------
 rpt/triangulator.cpp |   27 +-
 2 files changed, 592 insertions(+), 589 deletions(-)

diff --git a/media/RESULTS.md b/media/RESULTS.md
index 8611354..8388b66 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": 0.0206385,
+  "demosaicing": 0.000598167,
+  "avg_time_2d": 0.00822345,
+  "avg_time_3d": 3.54813e-05,
+  "fps": 112.904
 }
 {
   "triangulator_calls": 600,
-  "init_time": 2.64651e-06,
-  "undistort_time": 3.72878e-06,
-  "project_time": 7.91012e-07,
-  "match_time": 1.3786e-06,
-  "pairs_time": 2.28007e-07,
-  "pair_scoring_time": 6.05516e-06,
-  "grouping_time": 1.00762e-06,
-  "full_time": 7.78534e-06,
-  "merge_time": 3.16104e-06,
-  "post_time": 4.67212e-06,
-  "convert_time": 6.287e-08,
-  "total_time": 3.17519e-05
+  "init_time": 2.62541e-06,
+  "undistort_time": 3.73739e-06,
+  "project_time": 7.60795e-07,
+  "match_time": 1.39969e-06,
+  "pairs_time": 2.26192e-07,
+  "pair_scoring_time": 5.79049e-06,
+  "grouping_time": 9.75042e-07,
+  "full_time": 7.44867e-06,
+  "merge_time": 3.51708e-06,
+  "post_time": 4.28027e-06,
+  "convert_time": 5.8175e-08,
+  "total_time": 3.1055e-05
 }
 {
   "person_nums": {
@@ -45,52 +45,52 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 600,
-    "mean": 0.06137,
-    "median": 0.052692,
-    "std": 0.028754,
-    "sem": 0.001175,
-    "min": 0.036336,
-    "max": 0.189303,
+    "mean": 0.060962,
+    "median": 0.052484,
+    "std": 0.028624,
+    "sem": 0.00117,
+    "min": 0.036311,
+    "max": 0.188858,
     "recall-0.025": 0.0,
-    "recall-0.05": 0.341667,
+    "recall-0.05": 0.366667,
     "recall-0.1": 0.936667,
     "recall-0.15": 0.95,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 600,
     "ap-0.025": 0.0,
-    "ap-0.05": 0.198349,
-    "ap-0.1": 0.89113,
-    "ap-0.15": 0.911895,
+    "ap-0.05": 0.215605,
+    "ap-0.1": 0.891161,
+    "ap-0.15": 0.911559,
     "ap-0.25": 1.0,
     "ap-0.5": 1.0
   },
   "nose": {
     "count": 600,
-    "mean": 0.106588,
-    "median": 0.094594,
-    "std": 0.037095,
-    "sem": 0.001516,
-    "min": 0.025522,
-    "max": 0.26498,
-    "recall-0.025": 0.0,
+    "mean": 0.105757,
+    "median": 0.094634,
+    "std": 0.035993,
+    "sem": 0.001471,
+    "min": 0.024489,
+    "max": 0.260746,
+    "recall-0.025": 0.001667,
     "recall-0.05": 0.021667,
-    "recall-0.1": 0.57,
-    "recall-0.15": 0.883333,
-    "recall-0.25": 0.995,
+    "recall-0.1": 0.576667,
+    "recall-0.15": 0.89,
+    "recall-0.25": 0.998333,
     "recall-0.5": 1.0,
     "num_labels": 600
   },
   "shoulder_left": {
     "count": 600,
-    "mean": 0.035858,
-    "median": 0.026326,
-    "std": 0.033789,
-    "sem": 0.001381,
-    "min": 0.002501,
-    "max": 0.171365,
-    "recall-0.025": 0.456667,
-    "recall-0.05": 0.82,
+    "mean": 0.035821,
+    "median": 0.026476,
+    "std": 0.033776,
+    "sem": 0.00138,
+    "min": 0.002473,
+    "max": 0.171514,
+    "recall-0.025": 0.46,
+    "recall-0.05": 0.816667,
     "recall-0.1": 0.941667,
     "recall-0.15": 0.963333,
     "recall-0.25": 1.0,
@@ -99,30 +99,30 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_right": {
     "count": 600,
-    "mean": 0.044725,
-    "median": 0.033151,
-    "std": 0.040415,
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-    "recall-0.025": 0.333333,
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-    "recall-0.1": 0.911667,
-    "recall-0.15": 0.941667,
-    "recall-0.25": 1.0,
+    "mean": 0.044875,
+    "median": 0.032878,
+    "std": 0.041356,
+    "sem": 0.00169,
+    "min": 0.004517,
+    "max": 0.26572,
+    "recall-0.025": 0.331667,
+    "recall-0.05": 0.776667,
+    "recall-0.1": 0.913333,
+    "recall-0.15": 0.94,
+    "recall-0.25": 0.998333,
     "recall-0.5": 1.0,
     "num_labels": 600
   },
   "elbow_left": {
     "count": 600,
-    "mean": 0.044885,
-    "median": 0.035671,
-    "std": 0.036139,
+    "mean": 0.044585,
+    "median": 0.035103,
+    "std": 0.036154,
     "sem": 0.001477,
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-    "recall-0.025": 0.258333,
-    "recall-0.05": 0.78,
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+    "recall-0.05": 0.786667,
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     "recall-0.15": 0.953333,
     "recall-0.25": 1.0,
@@ -131,14 +131,14 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_right": {
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-    "median": 0.0314,
-    "std": 0.037255,
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-    "max": 0.305834,
+    "mean": 0.042661,
+    "median": 0.031367,
+    "std": 0.037706,
+    "sem": 0.001541,
+    "min": 0.004304,
+    "max": 0.322234,
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+    "recall-0.05": 0.821667,
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     "recall-0.15": 0.943333,
     "recall-0.25": 0.996667,
@@ -147,15 +147,15 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
     "count": 600,
-    "mean": 0.041456,
-    "median": 0.024274,
-    "std": 0.045842,
-    "sem": 0.001873,
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-    "recall-0.025": 0.516667,
-    "recall-0.05": 0.758333,
-    "recall-0.1": 0.895,
+    "mean": 0.040793,
+    "median": 0.024225,
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+    "sem": 0.001854,
+    "min": 0.000836,
+    "max": 0.326313,
+    "recall-0.025": 0.521667,
+    "recall-0.05": 0.77,
+    "recall-0.1": 0.898333,
     "recall-0.15": 0.943333,
     "recall-0.25": 0.996667,
     "recall-0.5": 1.0,
@@ -163,31 +163,31 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_right": {
     "count": 599,
-    "mean": 0.045939,
-    "median": 0.027958,
-    "std": 0.052067,
-    "sem": 0.002129,
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-    "max": 0.457433,
-    "recall-0.025": 0.443333,
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-    "recall-0.1": 0.89,
-    "recall-0.15": 0.908333,
-    "recall-0.25": 0.99,
+    "mean": 0.044678,
+    "median": 0.02687,
+    "std": 0.050652,
+    "sem": 0.002071,
+    "min": 0.002472,
+    "max": 0.457708,
+    "recall-0.025": 0.456667,
+    "recall-0.05": 0.783333,
+    "recall-0.1": 0.893333,
+    "recall-0.15": 0.911667,
+    "recall-0.25": 0.991667,
     "recall-0.5": 0.998333,
     "num_labels": 600
   },
   "hip_left": {
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-    "mean": 0.068231,
-    "median": 0.057583,
-    "std": 0.035521,
-    "sem": 0.001451,
-    "min": 0.02502,
-    "max": 0.215663,
+    "mean": 0.068763,
+    "median": 0.057992,
+    "std": 0.035423,
+    "sem": 0.001447,
+    "min": 0.025544,
+    "max": 0.215642,
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+    "recall-0.1": 0.885,
     "recall-0.15": 0.948333,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
@@ -195,14 +195,14 @@ Results of the model in various experiments on different datasets. \
   },
   "hip_right": {
     "count": 600,
-    "mean": 0.0855,
-    "median": 0.082345,
-    "std": 0.028363,
-    "sem": 0.001159,
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-    "max": 0.210242,
-    "recall-0.025": 0.01,
-    "recall-0.05": 0.051667,
+    "mean": 0.085671,
+    "median": 0.082582,
+    "std": 0.028486,
+    "sem": 0.001164,
+    "min": 0.019417,
+    "max": 0.210131,
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+    "recall-0.05": 0.056667,
     "recall-0.1": 0.871667,
     "recall-0.15": 0.95,
     "recall-0.25": 1.0,
@@ -211,82 +211,82 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_left": {
     "count": 600,
-    "mean": 0.058052,
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-    "recall-0.1": 0.91,
-    "recall-0.15": 0.921667,
+    "mean": 0.057169,
+    "median": 0.041844,
+    "std": 0.056709,
+    "sem": 0.002317,
+    "min": 0.014337,
+    "max": 0.41337,
+    "recall-0.025": 0.076667,
+    "recall-0.05": 0.695,
+    "recall-0.1": 0.911667,
+    "recall-0.15": 0.923333,
     "recall-0.25": 0.981667,
     "recall-0.5": 1.0,
     "num_labels": 600
   },
   "knee_right": {
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-    "recall-0.1": 0.921667,
+    "mean": 0.046846,
+    "median": 0.034283,
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+    "sem": 0.00168,
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+    "max": 0.30709,
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     "num_labels": 600
   },
   "ankle_left": {
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+    "count": 598,
+    "mean": 0.091286,
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   },
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+    "recall-0.25": 0.976667,
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     "num_labels": 600
   },
   "joint_recalls": {
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+    "recall-0.15": 0.93462,
+    "recall-0.25": 0.99385,
+    "recall-0.5": 0.99923
   }
 }
 {
   "total_parts": 8400,
-  "correct_parts": 8122,
-  "pcp": 0.966905
+  "correct_parts": 8128,
+  "pcp": 0.967619
 }
 ```
 
@@ -294,26 +294,26 @@ Results of the model in various experiments on different datasets. \
 
 ```json
 {
-  "img_loading": 0.042598,
-  "demosaicing": 0.000728448,
-  "avg_time_2d": 0.0148339,
-  "avg_time_3d": 0.000117913,
-  "fps": 63.7744
+  "img_loading": 0.0424233,
+  "demosaicing": 0.000707093,
+  "avg_time_2d": 0.0148645,
+  "avg_time_3d": 0.000118507,
+  "fps": 63.7344
 }
 {
   "triangulator_calls": 301,
-  "init_time": 2.94566e-06,
-  "undistort_time": 1.44382e-05,
-  "project_time": 2.17405e-06,
-  "match_time": 8.54757e-06,
-  "pairs_time": 4.47237e-06,
-  "pair_scoring_time": 2.70306e-05,
-  "grouping_time": 4.83738e-06,
-  "full_time": 2.72554e-05,
-  "merge_time": 1.0399e-05,
-  "post_time": 6.79547e-06,
-  "convert_time": 1.24645e-07,
-  "total_time": 0.000109261
+  "init_time": 2.85759e-06,
+  "undistort_time": 1.44325e-05,
+  "project_time": 2.22079e-06,
+  "match_time": 8.5159e-06,
+  "pairs_time": 4.48548e-06,
+  "pair_scoring_time": 2.66844e-05,
+  "grouping_time": 4.66512e-06,
+  "full_time": 2.71001e-05,
+  "merge_time": 1.16277e-05,
+  "post_time": 6.86999e-06,
+  "convert_time": 1.24289e-07,
+  "total_time": 0.000109822
 }
 {
   "person_nums": {
@@ -332,12 +332,12 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 477,
-    "mean": 0.048001,
-    "median": 0.042569,
-    "std": 0.014925,
-    "sem": 0.000684,
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-    "max": 0.116311,
+    "mean": 0.048033,
+    "median": 0.042733,
+    "std": 0.014947,
+    "sem": 0.000685,
+    "min": 0.030195,
+    "max": 0.118375,
     "recall-0.025": 0.0,
     "recall-0.05": 0.70021,
     "recall-0.1": 0.983229,
@@ -346,22 +346,22 @@ Results of the model in various experiments on different datasets. \
     "recall-0.5": 1.0,
     "num_labels": 477,
     "ap-0.025": 0.0,
-    "ap-0.05": 0.389107,
-    "ap-0.1": 0.731078,
-    "ap-0.15": 0.74682,
-    "ap-0.25": 0.74682,
-    "ap-0.5": 0.74682
+    "ap-0.05": 0.388387,
+    "ap-0.1": 0.728904,
+    "ap-0.15": 0.746165,
+    "ap-0.25": 0.746165,
+    "ap-0.5": 0.746165
   },
   "head": {
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-    "recall-0.05": 0.496855,
+    "mean": 0.054103,
+    "median": 0.050002,
+    "std": 0.024914,
+    "sem": 0.001142,
+    "min": 0.005111,
+    "max": 0.189881,
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+    "recall-0.05": 0.498952,
     "recall-0.1": 0.937107,
     "recall-0.15": 0.995807,
     "recall-0.25": 1.0,
@@ -370,14 +370,14 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_left": {
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-    "max": 0.136587,
-    "recall-0.025": 0.161426,
-    "recall-0.05": 0.727463,
+    "mean": 0.042381,
+    "median": 0.036815,
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+    "sem": 0.000947,
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+    "recall-0.05": 0.733753,
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     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -386,14 +386,14 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_right": {
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-    "mean": 0.049623,
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-    "recall-0.05": 0.561845,
+    "mean": 0.049767,
+    "median": 0.046023,
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+    "sem": 0.001063,
+    "min": 0.005303,
+    "max": 0.148245,
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+    "recall-0.05": 0.553459,
     "recall-0.1": 0.955975,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -402,13 +402,13 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_left": {
     "count": 477,
-    "mean": 0.04078,
-    "median": 0.032063,
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-    "sem": 0.001342,
-    "min": 0.003449,
-    "max": 0.326226,
-    "recall-0.025": 0.316562,
+    "mean": 0.040733,
+    "median": 0.032118,
+    "std": 0.029137,
+    "sem": 0.001336,
+    "min": 0.003472,
+    "max": 0.317898,
+    "recall-0.025": 0.314465,
     "recall-0.05": 0.756813,
     "recall-0.1": 0.953878,
     "recall-0.15": 0.997904,
@@ -418,62 +418,62 @@ Results of the model in various experiments on different datasets. \
   },
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@@ -482,14 +482,14 @@ 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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@@ -514,14 +514,14 @@ Results of the model in various experiments on different datasets. \
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@@ -530,15 +530,15 @@ Results of the model in various experiments on different datasets. \
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@@ -546,12 +546,12 @@ 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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 {
   "total_parts": 6678,
-  "correct_parts": 6619,
-  "pcp": 0.991165
+  "correct_parts": 6620,
+  "pcp": 0.991315
 }
 ```
 
@@ -1091,26 +1091,26 @@ Results of the model in various experiments on different datasets. \
 
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@@ -1167,14 +1167,14 @@ 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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@@ -1199,15 +1199,15 @@ Results of the model in various experiments on different datasets. \
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@@ -1215,14 +1215,14 @@ Results of the model in various experiments on different datasets. \
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@@ -1231,47 +1231,47 @@ Results of the model in various experiments on different datasets. \
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@@ -1279,98 +1279,98 @@ Results of the model in various experiments on different datasets. \
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+    "std": 0.060269,
+    "sem": 0.001578,
+    "min": 0.001995,
+    "max": 0.44695,
+    "recall-0.025": 0.354067,
+    "recall-0.05": 0.683527,
+    "recall-0.1": 0.867396,
+    "recall-0.15": 0.920027,
+    "recall-0.25": 0.97676,
+    "recall-0.5": 0.997266,
     "num_labels": 1463
   },
   "ankle_right": {
-    "count": 1445,
-    "mean": 0.053677,
-    "median": 0.031035,
-    "std": 0.067345,
-    "sem": 0.001772,
-    "min": 0.001539,
-    "max": 0.490198,
-    "recall-0.025": 0.382192,
-    "recall-0.05": 0.738356,
-    "recall-0.1": 0.853425,
-    "recall-0.15": 0.905479,
-    "recall-0.25": 0.962329,
-    "recall-0.5": 0.989726,
+    "count": 1446,
+    "mean": 0.051927,
+    "median": 0.030794,
+    "std": 0.064938,
+    "sem": 0.001708,
+    "min": 0.001857,
+    "max": 0.493842,
+    "recall-0.025": 0.386301,
+    "recall-0.05": 0.742466,
+    "recall-0.1": 0.871233,
+    "recall-0.15": 0.910274,
+    "recall-0.25": 0.961644,
+    "recall-0.5": 0.990411,
     "num_labels": 1460
   },
   "joint_recalls": {
     "num_labels": 18990,
-    "recall-0.025": 0.57341,
-    "recall-0.05": 0.85445,
-    "recall-0.1": 0.95808,
-    "recall-0.15": 0.97694,
-    "recall-0.25": 0.98999,
-    "recall-0.5": 0.99674
+    "recall-0.025": 0.57925,
+    "recall-0.05": 0.85692,
+    "recall-0.1": 0.96114,
+    "recall-0.15": 0.97825,
+    "recall-0.25": 0.99052,
+    "recall-0.5": 0.99695
   }
 }
 {
   "total_parts": 20444,
-  "correct_parts": 20199,
-  "pcp": 0.988016
+  "correct_parts": 20215,
+  "pcp": 0.988799
 }
 ```
 
@@ -5325,26 +5325,26 @@ 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": 0.278237,
+  "demosaicing": 0.0110612,
+  "avg_time_2d": 0.0240154,
+  "avg_time_3d": 0.000242046,
+  "fps": 28.3137
 }
 {
   "triangulator_calls": 121,
-  "init_time": 3.87942e-06,
-  "undistort_time": 1.88965e-05,
-  "project_time": 3.84835e-06,
-  "match_time": 1.2984e-05,
-  "pairs_time": 1.01412e-05,
-  "pair_scoring_time": 6.05492e-05,
-  "grouping_time": 1.17203e-05,
-  "full_time": 7.05481e-05,
-  "merge_time": 2.97129e-05,
-  "post_time": 7.14949e-06,
-  "convert_time": 1.34868e-07,
-  "total_time": 0.000229801
+  "init_time": 3.4108e-06,
+  "undistort_time": 1.9004e-05,
+  "project_time": 3.96777e-06,
+  "match_time": 1.33092e-05,
+  "pairs_time": 1.08128e-05,
+  "pair_scoring_time": 6.1806e-05,
+  "grouping_time": 1.16601e-05,
+  "full_time": 7.14101e-05,
+  "merge_time": 3.26368e-05,
+  "post_time": 7.33497e-06,
+  "convert_time": 1.39355e-07,
+  "total_time": 0.00023573
 }
 {
   "person_nums": {
@@ -5363,21 +5363,21 @@ Results of the model in various experiments on different datasets. \
   },
   "mpjpe": {
     "count": 363,
-    "mean": 0.025726,
-    "median": 0.024997,
-    "std": 0.00724,
-    "sem": 0.000381,
-    "min": 0.011774,
-    "max": 0.052562,
-    "recall-0.025": 0.501377,
+    "mean": 0.025709,
+    "median": 0.024834,
+    "std": 0.007209,
+    "sem": 0.000379,
+    "min": 0.011746,
+    "max": 0.051988,
+    "recall-0.025": 0.515152,
     "recall-0.05": 0.997245,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 363,
-    "ap-0.025": 0.271699,
-    "ap-0.05": 0.996479,
+    "ap-0.025": 0.282931,
+    "ap-0.05": 0.996426,
     "ap-0.1": 1.0,
     "ap-0.15": 1.0,
     "ap-0.25": 1.0,
@@ -5385,14 +5385,14 @@ Results of the model in various experiments on different datasets. \
   },
   "head": {
     "count": 363,
-    "mean": 0.027328,
-    "median": 0.022736,
-    "std": 0.01683,
-    "sem": 0.000885,
-    "min": 0.00115,
-    "max": 0.085467,
+    "mean": 0.027303,
+    "median": 0.023105,
+    "std": 0.016677,
+    "sem": 0.000877,
+    "min": 0.001375,
+    "max": 0.086144,
     "recall-0.025": 0.573003,
-    "recall-0.05": 0.895317,
+    "recall-0.05": 0.900826,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5401,30 +5401,30 @@ Results of the model in various experiments on different datasets. \
   },
   "shoulder_left": {
     "count": 363,
-    "mean": 0.027044,
-    "median": 0.021957,
-    "std": 0.02084,
-    "sem": 0.001095,
-    "min": 0.002793,
-    "max": 0.149897,
-    "recall-0.025": 0.589532,
-    "recall-0.05": 0.887052,
+    "mean": 0.027108,
+    "median": 0.022,
+    "std": 0.020752,
+    "sem": 0.001091,
+    "min": 0.002767,
+    "max": 0.150529,
+    "recall-0.025": 0.592287,
+    "recall-0.05": 0.892562,
     "recall-0.1": 0.986226,
-    "recall-0.15": 1.0,
+    "recall-0.15": 0.997245,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
     "num_labels": 363
   },
   "shoulder_right": {
     "count": 363,
-    "mean": 0.022957,
-    "median": 0.020511,
-    "std": 0.012804,
-    "sem": 0.000673,
-    "min": 0.003064,
-    "max": 0.101875,
-    "recall-0.025": 0.628099,
-    "recall-0.05": 0.961433,
+    "mean": 0.02312,
+    "median": 0.020238,
+    "std": 0.012706,
+    "sem": 0.000668,
+    "min": 0.002849,
+    "max": 0.10193,
+    "recall-0.025": 0.62259,
+    "recall-0.05": 0.966942,
     "recall-0.1": 0.997245,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5433,13 +5433,13 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_left": {
     "count": 363,
-    "mean": 0.022517,
-    "median": 0.019538,
-    "std": 0.015673,
-    "sem": 0.000824,
-    "min": 0.001254,
-    "max": 0.207405,
-    "recall-0.025": 0.680441,
+    "mean": 0.022561,
+    "median": 0.019468,
+    "std": 0.015633,
+    "sem": 0.000822,
+    "min": 0.001582,
+    "max": 0.207353,
+    "recall-0.025": 0.68595,
     "recall-0.05": 0.961433,
     "recall-0.1": 0.997245,
     "recall-0.15": 0.997245,
@@ -5449,14 +5449,14 @@ Results of the model in various experiments on different datasets. \
   },
   "elbow_right": {
     "count": 363,
-    "mean": 0.018557,
-    "median": 0.016702,
-    "std": 0.010298,
-    "sem": 0.000541,
-    "min": 0.002522,
-    "max": 0.082821,
+    "mean": 0.018544,
+    "median": 0.016655,
+    "std": 0.010242,
+    "sem": 0.000538,
+    "min": 0.002603,
+    "max": 0.082689,
     "recall-0.025": 0.807163,
-    "recall-0.05": 0.991736,
+    "recall-0.05": 0.988981,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5465,14 +5465,14 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_left": {
     "count": 363,
-    "mean": 0.023647,
-    "median": 0.018944,
-    "std": 0.018362,
-    "sem": 0.000965,
-    "min": 0.002721,
-    "max": 0.199952,
-    "recall-0.025": 0.68595,
-    "recall-0.05": 0.928375,
+    "mean": 0.023435,
+    "median": 0.018811,
+    "std": 0.018148,
+    "sem": 0.000954,
+    "min": 0.0023,
+    "max": 0.200226,
+    "recall-0.025": 0.688705,
+    "recall-0.05": 0.933884,
     "recall-0.1": 0.991736,
     "recall-0.15": 0.997245,
     "recall-0.25": 1.0,
@@ -5481,14 +5481,14 @@ Results of the model in various experiments on different datasets. \
   },
   "wrist_right": {
     "count": 363,
-    "mean": 0.019782,
-    "median": 0.017758,
-    "std": 0.011189,
-    "sem": 0.000588,
-    "min": 0.001634,
-    "max": 0.076393,
-    "recall-0.025": 0.757576,
-    "recall-0.05": 0.975207,
+    "mean": 0.019636,
+    "median": 0.017778,
+    "std": 0.011098,
+    "sem": 0.000583,
+    "min": 0.003242,
+    "max": 0.077536,
+    "recall-0.025": 0.76584,
+    "recall-0.05": 0.980716,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5497,14 +5497,14 @@ Results of the model in various experiments on different datasets. \
   },
   "hip_left": {
     "count": 363,
-    "mean": 0.031192,
-    "median": 0.026563,
-    "std": 0.017009,
-    "sem": 0.000894,
-    "min": 0.005051,
-    "max": 0.116967,
-    "recall-0.025": 0.438017,
-    "recall-0.05": 0.848485,
+    "mean": 0.031051,
+    "median": 0.026439,
+    "std": 0.016983,
+    "sem": 0.000893,
+    "min": 0.005104,
+    "max": 0.117092,
+    "recall-0.025": 0.446281,
+    "recall-0.05": 0.853994,
     "recall-0.1": 0.997245,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5513,14 +5513,14 @@ Results of the model in various experiments on different datasets. \
   },
   "hip_right": {
     "count": 363,
-    "mean": 0.031175,
-    "median": 0.028448,
-    "std": 0.017051,
-    "sem": 0.000896,
-    "min": 0.003029,
-    "max": 0.138279,
-    "recall-0.025": 0.371901,
-    "recall-0.05": 0.900826,
+    "mean": 0.031582,
+    "median": 0.028644,
+    "std": 0.017376,
+    "sem": 0.000913,
+    "min": 0.003061,
+    "max": 0.138503,
+    "recall-0.025": 0.366391,
+    "recall-0.05": 0.892562,
     "recall-0.1": 0.991736,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
@@ -5529,15 +5529,15 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_left": {
     "count": 363,
-    "mean": 0.028398,
-    "median": 0.020711,
-    "std": 0.023128,
-    "sem": 0.001216,
-    "min": 0.001921,
-    "max": 0.12193,
-    "recall-0.025": 0.633609,
-    "recall-0.05": 0.856749,
-    "recall-0.1": 0.977961,
+    "mean": 0.028515,
+    "median": 0.021075,
+    "std": 0.023189,
+    "sem": 0.001219,
+    "min": 0.00224,
+    "max": 0.123462,
+    "recall-0.025": 0.61708,
+    "recall-0.05": 0.853994,
+    "recall-0.1": 0.972452,
     "recall-0.15": 1.0,
     "recall-0.25": 1.0,
     "recall-0.5": 1.0,
@@ -5545,13 +5545,13 @@ Results of the model in various experiments on different datasets. \
   },
   "knee_right": {
     "count": 363,
-    "mean": 0.023753,
-    "median": 0.020598,
-    "std": 0.013656,
-    "sem": 0.000718,
-    "min": 0.002869,
-    "max": 0.067651,
-    "recall-0.025": 0.595041,
+    "mean": 0.023905,
+    "median": 0.020469,
+    "std": 0.013552,
+    "sem": 0.000712,
+    "min": 0.00231,
+    "max": 0.067798,
+    "recall-0.025": 0.586777,
     "recall-0.05": 0.939394,
     "recall-0.1": 1.0,
     "recall-0.15": 1.0,
@@ -5561,14 +5561,14 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_left": {
     "count": 363,
-    "mean": 0.028378,
-    "median": 0.022211,
-    "std": 0.022536,
-    "sem": 0.001184,
-    "min": 0.002738,
-    "max": 0.179868,
-    "recall-0.025": 0.570248,
-    "recall-0.05": 0.895317,
+    "mean": 0.028076,
+    "median": 0.022154,
+    "std": 0.022505,
+    "sem": 0.001183,
+    "min": 0.002848,
+    "max": 0.178544,
+    "recall-0.025": 0.575758,
+    "recall-0.05": 0.900826,
     "recall-0.1": 0.980716,
     "recall-0.15": 0.99449,
     "recall-0.25": 1.0,
@@ -5577,15 +5577,15 @@ Results of the model in various experiments on different datasets. \
   },
   "ankle_right": {
     "count": 363,
-    "mean": 0.029714,
-    "median": 0.022134,
-    "std": 0.026933,
+    "mean": 0.029383,
+    "median": 0.022253,
+    "std": 0.026946,
     "sem": 0.001416,
-    "min": 0.003345,
-    "max": 0.265506,
+    "min": 0.003171,
+    "max": 0.279154,
     "recall-0.025": 0.573003,
-    "recall-0.05": 0.865014,
-    "recall-0.1": 0.969697,
+    "recall-0.05": 0.870523,
+    "recall-0.1": 0.975207,
     "recall-0.15": 0.99449,
     "recall-0.25": 0.997245,
     "recall-0.5": 1.0,
@@ -5593,10 +5593,10 @@ Results of the model in various experiments on different datasets. \
   },
   "joint_recalls": {
     "num_labels": 4719,
-    "recall-0.025": 0.60733,
-    "recall-0.05": 0.91524,
-    "recall-0.1": 0.99046,
-    "recall-0.15": 0.99788,
+    "recall-0.025": 0.60691,
+    "recall-0.05": 0.91651,
+    "recall-0.1": 0.99068,
+    "recall-0.15": 0.99746,
     "recall-0.25": 0.99958,
     "recall-0.5": 1.0
   }
diff --git a/rpt/triangulator.cpp b/rpt/triangulator.cpp
index 1d9b049..f60fbb9 100644
--- a/rpt/triangulator.cpp
+++ b/rpt/triangulator.cpp
@@ -1787,7 +1787,7 @@ 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);
     for (size_t i = 0; i < num_poses; ++i)
     {
         const auto &pose = poses_3d[i];
@@ -1797,11 +1797,12 @@ std::vector<std::array<float, 4>> TriangulatorInternal::merge_group(
             float score = pose[j][3];
             if (score > min_score)
             {
-                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;
             }
         }
     }
@@ -1915,7 +1916,7 @@ 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 +1925,13 @@ 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;
             }
         }
     }