fix: face tracker embedding threshold — reject similarity < 0.5, tighten fallback to >0.75

scripts/utils/face_tracker.py

@@ -111,6 +111,7 @@ def match_faces(
     similarity_threshold: float = 0.7,
     distance_threshold: float = 100.0,
     use_embedding: bool = True,
+    frame_gap: int = 1,
 ) -> Dict[int, int]:
     """
     Match current frame faces to previous frame faces
@@ -122,6 +123,7 @@ def match_faces(
         similarity_threshold: Minimum embedding similarity for matching
         distance_threshold: Maximum bbox center distance for matching
         use_embedding: Whether to use embedding similarity
+        frame_gap: Number of frames between current and previous (1=adjacent)
     
     Returns:
         Dict mapping current_face_index -> previous_face_index (or -1 if new)
@@ -165,14 +167,21 @@ def match_faces(
             
             score = 0.0
             
+            # Always reject if embedding similarity is too low (different person)
+            if use_embedding and curr_emb and prev_emb and similarity < 0.5:
+                continue
+            
             if iou > iou_threshold and similarity > similarity_threshold:
                 score = iou + similarity
-            elif iou > 0.5:
-                score = iou * 2
+            elif iou > 0.5 and similarity > 0.65:
+                score = iou * 1.5 + similarity * 0.5
             elif similarity > 0.85:
                 score = similarity * 2
-            elif distance < distance_threshold and similarity > 0.6:
+            elif similarity > 0.75 and distance < distance_threshold:
                 score = similarity - distance / 1000
+            # For frame gaps (tracking lost and recovered), require higher confidence
+            elif frame_gap > 1 and similarity > 0.8 and iou > 0.2:
+                score = similarity + iou
             
             if score > best_score:
                 best_score = score
@@ -220,6 +229,7 @@ def track_faces(
     
     prev_faces = []
     prev_trace_ids = []
+    prev_frame_num = None
     
     print(f"\nTracking faces across {len(sorted_frames)} frames...")
     print(f"Parameters: iou={iou_threshold}, similarity={similarity_threshold}, distance={distance_threshold}")
@@ -227,6 +237,9 @@ def track_faces(
     
     for frame_num_str, frame_data in sorted_frames:
         frame_num = int(frame_num_str)
+        frame_gap = frame_num - prev_frame_num if prev_frame_num is not None else 1
+        prev_frame_num = frame_num
+        
         faces = frame_data.get("faces", [])
         
         if not faces:
@@ -241,6 +254,7 @@ def track_faces(
             similarity_threshold,
             distance_threshold,
             use_embedding,
+            frame_gap,
         )
         
         trace_ids = []