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CVPR
2009
IEEE

Multi-view 3D Human Pose Estimation combining Single-frame Recovery, Temporal Integration and Model Adaptation

14 years 10 months ago
Multi-view 3D Human Pose Estimation combining Single-frame Recovery, Temporal Integration and Model Adaptation
We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model adaptation. Single-frame pose recovery consists of a hypothesis generation stage, where candidate 3D poses are generated based on hierarchical shape matching in the individual camera views. In the subsequent hypothesis verification stage, candidate 3D poses are re-projected to the other camera views and ranked according to a multi-view matching score. Temporal integration consists of computing best trajectories combining a motion model and observations in a Viterbi-style maximum likelihood approach. Poses that lie on the best trajectories are used to generate and adapt a texture model, which in turn enriches the shape component used for pose recovery. We demonstrate that our approach outperforms the state-of-the-art in experiments with large a...
Dariu M. Gavrila, Michael Hofmann
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Dariu M. Gavrila, Michael Hofmann
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