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From Canonical Poses to 3D Motion Capture Using a Single Camera

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

We combine detection and tracking techniques to achieve robust 3D 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 3D poses between consecutive detections, and finally refining them over the whole sequence using a generative model. We demonstrate our approach in the cases of golf motions filmed using a static camera and walking motions acquired using a potentially moving one. We will show that our approach, although monocular, is both metrically accurate because it integrates information over many frames and robust because it can recover from a few misdetections.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:32 ,  Issue: 7 )

Date of Publication:

July 2010

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