This work uses crowdsourcing to obtain motion capture data from video recordings. The data is obtained by information workers who click repeatedly to indicate body configurations in the frames of a video, resulting in a model of 2D structure over time. We discuss techniques to optimize the tracking task and strategies for maximizing accuracy and efficiency. We show visualizations of a variety of motions captured with our pipeline then apply reconstruction techniques to derive 3D structure.
@article{arxiv.1204.3596,
title = {Markerless Motion Capture in the Crowd},
author = {Ian Spiro and Thomas Huston and Christoph Bregler},
journal= {arXiv preprint arXiv:1204.3596},
year = {2012}
}
Comments
Presented at Collective Intelligence conference, 2012 (arXiv:1204.2991)