再投影誤差による破綻フレームの除外および窓の時間指定の実装と実験陽設定の更新

src/head_pose.py

@@ -55,6 +55,8 @@ class HeadPoseEstimator:
         image_points = self.build_image_points(landmarks)
         if image_points is None:
             return HeadPoseEstimation(False, failure_reason="insufficient_landmarks")
+        # Outer eye corners (landmarks 33 and 263) are model points 2 and 3.
+        eye_distance = math.hypot(image_points[3][0] - image_points[2][0], image_points[3][1] - image_points[2][1])
         try:
             import cv2
             import numpy as np
@@ -74,13 +76,24 @@ class HeadPoseEstimator:
             error = float(np.sqrt(np.mean(np.sum((projected.reshape(-1, 2) - image) ** 2, axis=1))))
         except Exception:
             return HeadPoseEstimation(False, failure_reason="solvepnp_failed")
-        return self.result_from_angles(angles, error)
+        return self.result_from_angles(angles, error, eye_distance_px=eye_distance)
 
     def result_from_angles(
         self, angles: tuple[float, float, float], reprojection_error: float | None = None,
+        eye_distance_px: float | None = None,
     ) -> HeadPoseEstimation:
-        """Validate calculated angles and construct a normalized result."""
+        """Validate calculated angles and construct a normalized result.
+
+        When ``max_reprojection_error_ratio`` is set, a pose whose reprojection error
+        exceeds that multiple of ``eye_distance_px`` is rejected: it is a degenerate
+        solution (typically a very small or leaving face), not a noisy measurement.
+        """
         normalized = self.normalize_angles(angles)
+        ratio = self.config.max_reprojection_error_ratio
+        if (ratio > 0.0 and reprojection_error is not None and eye_distance_px is not None
+                and eye_distance_px > 0.0 and reprojection_error > ratio * eye_distance_px):
+            return HeadPoseEstimation(False, *normalized, reprojection_error=reprojection_error,
+                                      failure_reason="reprojection_error_too_large")
         if any(not math.isfinite(value) or abs(value) > self.config.max_abs_angle for value in normalized):
             return HeadPoseEstimation(False, *normalized, reprojection_error=reprojection_error,
                                       failure_reason="angle_out_of_range")