Landmarks are estimates from pixels

Pose models infer likely joint positions from an image. Landmark visibility and confidence help indicate when a joint may be occluded or uncertain, but they are not a guarantee of correctness. A hand behind the torso or a foot at the edge of the frame can produce unstable estimates even when the camera is running normally.

Thresholds should match human movement

A rigid detector can reject valid poses because people differ in arm length, shoulder slope, stance, and camera angle. Prefer ratios normalised to shoulder span or torso height, tolerate modest left-right differences, and require a few consecutive valid frames. The detector should also reset its stability counter when the user leaves the pose.

Make the camera lifecycle explicit

Check for navigator.mediaDevices and getUserMedia support, request permission from a clear user action, attach the returned stream to a muted playsInline video element, and wait for playback before processing frames. Clean up tracks, animation frames, and the landmarker when the component unmounts. Report permission denial and model-download failures visibly.

Recover gracefully

A robust interface distinguishes camera permission errors from missing landmarks. If the camera is working but the body is cropped, show framing guidance. If the model cannot load, offer a retry and retain an accessible explanation. Progress should reflect observed milestones, not an arbitrary timer.

Educational content only. This article is not medical advice and does not replace guidance from a qualified professional.