Pose Estimation
Also known as: human pose detection, body keypoint detection
Pose estimation is the computer-vision process that detects the positions of major body joints (keypoints) in each video frame, producing the skeleton that SwingVantage uses to measure angles and movement patterns.
Pose estimation runs a neural network over each video frame to locate landmarks like shoulders, elbows, wrists, hips, knees, and ankles. It is the first processing step after the quality gate and the foundation for all motion metrics. Accuracy depends on visibility: occluded joints (hidden by clothing, body rotation, or poor lighting) produce lower-confidence keypoints that are labeled accordingly. SwingVantage uses on-device pose estimation where possible to keep video private.
Example
Pose estimation places 33 body landmarks on each frame of a golf swing, letting the engine compute hip-to-shoulder separation angle through impact.
Why it matters
Without reliable pose estimation, angles and timing metrics cannot be computed at all. It is the step where good video setup pays off most.
Related terms
- Skeleton OverlayA skeleton overlay is the on-screen visualization of detected body joints and the lines connecting them, drawn over your video so you can see exactly what the system tracked.
- Landmark TrackingLandmark tracking follows the position of each detected body keypoint across consecutive video frames, creating a time-series trajectory for every joint that enables timing and velocity measurements.
- Mobile Motion CaptureMobile motion capture is the process of using a smartphone camera and on-device pose estimation to track body movement in real time or from a recorded clip — no specialized hardware required.
- Video Quality ScoreA Video Quality Score is a pre-analysis rating (0–100) that tells you how usable a submitted clip is before pose estimation begins — catching bad angles, motion blur, or poor lighting early.
Put this into your swing
SwingVantage can spot this in your own swing — free to start.