Monocular camera tracks wrist movements using passive markers and anchors
MonoEgo: Monocular Metric Egocentric Demonstration Capture with Passive Wrist Constellations and Sparse Workstation Anchors
Robotics
Summary
Tracking hand and wrist movements usually needs special devices and synced cameras. The authors developed MonoEgo, a system that uses one regular camera to watch passive markers on the wrist and some fixed points in the workspace. Their method reconstructs hand motion accurately without needing active sensors, even when some fixed points are out of sight. This approach lowers the complexity and hardware needed for capturing hand demonstrations. However, more tests are needed to understand how well it works dynamically and in real use.
What this means in practice
- •For robotics engineers: Create robotic systems that learn from human wrist motion captured without active sensors using a single camera setup.
- •For ergonomics specialists: Analyze hand and wrist movements in workplace settings using passive markers and minimal camera equipment.
Authors
Jie Xu, Kangjin Yu, Ziyi Jin, Beichen Wang, Zhongpu Xia
Abstract
Image-aligned metric demonstrations often require dedicated tracking hardware and synchronization across devices. We present MonoEgo, a capture system that replaces active wrist instrumentation with offline monocular reconstruction. One 90-FPS global-shutter camera observes calibrated passive wrist constellations, sparse workstation anchors, and the scene on a shared image clock. MonoTag SLAM combines marker corners with ORB geometry and uses visual evidence to reject ambiguous planar-marker poses. Its metric Atlas supports interval scale re-anchoring, verified map merging, and retrospective localization of earlier frames supported by the final map. Camera and wrist-constellation outputs retain validity and map provenance, and unsupported motion is left missing. Experiments show metric tracking beyond continuous anchor visibility, reconnection of supported map components, and recovery of some missing camera poses. Comparisons against a multisensor camera reference and separate stationary-constellation tests characterize trajectory agreement and precision while revealing incomplete coverage and residual geometric uncertainty. The results indicate that passive fixtures and offline reconstruction can reduce capture-side requirements. Dynamic accuracy, deployment, and downstream policy benefits require further study.