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Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture

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4 Author(s)
Fossati, A. ; Ecole Polytech. Fed. de Lausanne, Lausanne ; Dimitrijevic, M. ; Lepetit, V. ; Fua, P.

We combine detection and tracking techniques to achieve robust 3-D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to infer 3-D poses between consecutive detections, and finally refining them over the whole sequence using a generative model. We demonstrate our approach in the case of people walking against cluttered backgrounds and filmed using a moving camera, which precludes the use of simple background subtraction techniques. In this case, the easy-to-detect posture is the one that occurs at the end of each step when people have their legs furthest apart.

Published in:

Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on

Date of Conference:

17-22 June 2007