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Multi-person total motion capture is extremely challenging when it comes tohandle severe occlusions, different reconstruction granularities from body toface and hands, drastically changing observation scales and fast bodymovements. To overcome these challenges above, we contribute a lightweighttotal motion capture system for multi-person interactive scenarios using onlysparse multi-view cameras. By contributing a novel hand and face bootstrappingalgorithm, our method is capable of efficient localization and accurateassociation of the hands and faces even on severe occluded occasions. Weleverage both pose regression and keypoints detection methods and furtherpropose a unified two-stage parametric fitting method for achievingpixel-aligned accuracy. Moreover, for extremely self-occluded poses and closeinteractions, a novel feedback mechanism is proposed to propagate thepixel-aligned reconstructions into the next frame for more accurateassociation. Overall, we propose the first light-weight total capture systemand achieves fast, robust and accurate multi-person total motion captureperformance. The results and experiments show that our method achieves moreaccurate results than existing methods under sparse-view setups.

Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras