ArUco + MediaPipe Hand Tracking
A computer-vision prototype combining calibrated ArUco pose estimation, MediaPipe hand landmarks and a Kalman-based fusion path with real-time visualisation and recordable experiment outputs.
Role
- Developer
- Computer vision prototyping
Stack
- Python
- OpenCV
- MediaPipe
- NumPy
- Pandas
- Kalman filtering
Problem
Marker-based pose estimation and markerless hand tracking offer different strengths; the prototype explores how they can be observed together and compared through one calibrated workflow.
Constraints
- Accurate ArUco 3D pose estimation depends on camera calibration and known marker dimensions.
- ArUco observations are sensitive to occlusion, while MediaPipe wrist landmarks are image-space estimates.
- The same application must support live cameras, recorded video and headless data capture.
My contribution
- Structured acquisition, detection, fusion and utility modules around a single command-line entry point.
- Integrated camera calibration, per-frame CSV logging, raw and processed video recording and optional ground-truth comparison.
- Added selectable ArUco, MediaPipe and fusion modes so the signals can be inspected independently or together.
Architecture / methodology
- Estimate marker pose with OpenCV ArUco and detect hand landmarks with MediaPipe Hands.
- Associate configured marker IDs with left and right hands and combine observations through the fusion module.
- Capture timestamps, processing stages, detections and fused positions for later analysis.
Evaluation
- Compare ArUco, MediaPipe and fusion modes using the same video or camera source.
- Supply optional ground-truth positions in CSV form for frame-aligned comparison.
- Inspect stage timings and exported frame data rather than claiming an unsupported accuracy result.
Results
- The repository documents a runnable prototype and repeatable calibration/data-capture workflow.
- No accuracy or runtime benchmark is claimed because the public evidence does not include a completed evaluation report.
Evidence and links
The public repository documents ArUco pose detection, MediaPipe hand landmarks, fusion, calibration and CSV/video recording.
Public repository README (opens in a new tab)The repository was published with its initial commit in June 2026.
Public GitHub commit history (opens in a new tab)