Moved 2D confidence scaling to a later step.

rpt/triangulator.cpp

@@ -828,6 +828,27 @@ 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);
     }
 
@@ -1430,11 +1451,7 @@ std::pair<std::vector<std::array<float, 4>>, float> TriangulatorInternal::triang
         if (mask[i])
         {
             float scoreT = 0.5 * (score1[i] + score2[i]);
-            float scoreP = 0.5 * (pose1[i][2] + pose2[i][2]);
+            pose3d[i][3] = scoreT;
-
-            // Since the triangulation score is less sensitive and generally higher,
-            // weight it stronger to balance the two scores.
-            pose3d[i][3] = 0.9 * scoreT + 0.1 * scoreP;
         }
     }
 

scripts/test_skelda_dataset.py

@@ -41,7 +41,7 @@ default_min_bbox_score = 0.3
 
 # Describes how good two 2D poses need to match each other to create a valid triangulation
 # If the quality of the 2D detections is poor, use a lower value
-default_min_match_score = 0.91
+default_min_match_score = 0.94
 
 # Describes the minimum number of camera pairs that need to detect the same person
 # If the number of cameras is high, and the views are not occluded, use a higher value
@@ -55,7 +55,7 @@ datasets = {
     "human36m": {
         "path": "/datasets/human36m/skelda/pose_test.json",
         "take_interval": 5,
-        "min_match_score": 0.92,
+        "min_match_score": 0.95,
         "min_group_size": 1,
         "min_bbox_score": 0.4,
         "min_bbox_area": 0.1 * 0.1,
@@ -68,7 +68,7 @@ datasets = {
         # "cams": ["00_03", "00_06", "00_12", "00_13", "00_23", "00_15", "00_10", "00_21", "00_09", "00_01"],
         # "cams": [],
         "take_interval": 3,
-        "min_match_score": 0.92,
+        "min_match_score": 0.95,
         "use_scenes": ["160906_pizza1", "160422_haggling1", "160906_ian5"],
         "min_group_size": 1,
         # "min_group_size": 4,
@@ -79,25 +79,25 @@ datasets = {
         "path": "/datasets/mvor/skelda/all.json",
         "take_interval": 1,
         "with_depth": False,
-        "min_match_score": 0.80,
+        "min_match_score": 0.85,
         "min_bbox_score": 0.25,
     },
     "campus": {
         "path": "/datasets/campus/skelda/test.json",
         "take_interval": 1,
-        "min_match_score": 0.89,
+        "min_match_score": 0.92,
         "min_bbox_score": 0.5,
     },
     "shelf": {
         "path": "/datasets/shelf/skelda/test.json",
         "take_interval": 1,
-        "min_match_score": 0.92,
+        "min_match_score": 0.95,
         "min_group_size": 2,
     },
     "ikeaasm": {
         "path": "/datasets/ikeaasm/skelda/test.json",
         "take_interval": 2,
-        "min_match_score": 0.89,
+        "min_match_score": 0.92,
         "min_bbox_score": 0.20,
     },
     "chi3d": {
@@ -107,21 +107,20 @@ datasets = {
     "tsinghua": {
         "path": "/datasets/tsinghua/skelda/test.json",
         "take_interval": 3,
-        "min_match_score": 0.92,
+        "min_match_score": 0.95,
         "min_group_size": 2,
     },
     "human36m_wb": {
         "path": "/datasets/human36m/skelda/wb/test.json",
         "take_interval": 100,
         "min_bbox_score": 0.4,
-        "min_match_score": 0.93,
         "batch_poses": False,
     },
     "egohumans_tagging": {
         "path": "/datasets/egohumans/skelda/all.json",
         "take_interval": 2,
         "subset": "tagging",
-        "min_match_score": 0.89,
+        "min_match_score": 0.92,
         "min_group_size": 2,
         "min_bbox_score": 0.2,
         "min_bbox_area": 0.05 * 0.05,

scripts/test_triangulate.py

@@ -19,7 +19,7 @@ whole_body = {
     "hands": False,
 }
 config = {
-    "min_match_score": 0.91,
+    "min_match_score": 0.94,
     "min_group_size": 1,
     "min_bbox_score": 0.3,
     "min_bbox_area": 0.1 * 0.1,