VideoMocap: Modeling Physically Realistic Human Motion From Monocular Video Sequences
Xiaolin Wei, Jinxiang Chai
In ACM Transactions on Graphics, 29(4), July 2010.
Abstract: This paper presents a video-based motion modeling technique for capturing physically realistic human motion from monocular video sequences. We formulate the video-based motion modeling process in an image-based keyframe animation framework. The system first computes camera parameters, human skeletal size, and a small number of 3D key poses from video and then uses 2D image measurements at intermediate frames to automatically calculate the "in between" poses. During reconstruction, we leverage Newtonian physics, contact constraints, and 2D image measurements to simultaneously reconstruct full-body poses, joint torques, and contact forces. We have demonstrated the power and effectiveness of our system by generating a wide variety of physically realistic human actions from uncalibrated monocular video sequences such as sports video footage.
Keyword(s): data-driven animation, interactive 3D visual tracking, performance animation, physics-based animation, video-based motion capture, vision for graphics
@article{Wei:2010:VMP,
author = {Xiaolin Wei and Jinxiang Chai},
title = {VideoMocap: Modeling Physically Realistic Human Motion From Monocular Video Sequences},
journal = {ACM Transactions on Graphics},
volume = {29},
number = {4},
pages = {42:1--42:10},
month = jul,
year = {2010},
}
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