Movement analysis
Track wrists, knees and other joints to visualize motion through a sampled video.
Detect body joints, inspect skeleton overlays, trace movement and export actual pose landmarks frame by frame. AI inference happens in your browser, not on our servers.
Upload media, configure sampling, analyze, and inspect your results.
PNG, JPG, WebP or browser-decodable video
Files stay on this device · up to 180 MBChoose a media file to estimate the analysis workload.
Sample data is clearly labeled synthetic. Real pose results require the free MediaPipe model and an initial internet connection. No media file is transmitted by this app.
| Joint | X | Y | Z | Visible |
|---|---|---|---|---|
| Analysis results will appear here. | ||||
X/Y are normalized image coordinates, not physical distances. Z is model-relative, not centimeters. Estimated world coordinates are included in the JSON and optional world CSV where available.
Track wrists, knees and other joints to visualize motion through a sampled video.
Render joints, limb connections and visibility-filtered labels on top of a frame.
Export normalized landmarks, optional model-estimated world coordinates and project JSON without an account.
Yes, when you click Analyze the page loads Google's free MediaPipe Pose Landmarker model and performs inference locally. The sample button uses synthetic demonstration values, which are labeled explicitly.
The app does not upload media. The MediaPipe JavaScript, WebAssembly runtime and model are initially fetched from external hosts. MediaPipe may collect library usage metrics; see their privacy information. Self-host those files to eliminate the runtime CDN dependency.
Hidden, occluded, fast-moving or out-of-frame joints may not be predicted reliably. The visibility cutoff controls which predictions are drawn, but the raw output remains available in exported data.
No. This tool provides approximate computer-vision estimates, not validated clinical or biomechanical assessments. Angle calculations use 2D image coordinates and change with camera perspective.
No. Video export is silent and includes only analyzed sample frames. It uses real-time browser Canvas recording, so timing and codec support vary. CSV and JSON are the most faithful exports for frame-by-frame measurements.
Preparing your analysis…
Estimate pose landmarks from a photo or sampled video, then review trajectories and approximate angles. Treat the output as visual data for exploration, not calibrated measurement or identity tracking.
Example: For a two-second side-view exercise clip, inspect the reported hip and knee landmarks across sampled frames, note where detections disappear, and export the reviewed angle estimates for further analysis.
Limits and privacy: The tool accepts up to four people and 420 sampled frames, with video duration capped at 120 seconds. Model/runtime assets are fetched from external hosts after explicit setup and may disclose the visitor IP; actual inference remains unverified. World coordinates and 2D angles are estimates, person ordering is not persistent identity, and missing detections remain gaps. Browser-recorded WebM is silent and may vary by browser.