Multiple Cues used in Model-Based Human Motion Capture

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Multiple Cues used in Model-Based Human Motion Capture
Human motion capture has lately been the object of much attention due to commercial interests. A ”touch free” computer vision solution to the problem is desirable to avoid the intrusiveness of standard capture devices. The object to be monitored is known a priori which suggest to include a human model in the capture process. In this paper we use a model-based approach known as the analysis-bysynthesis approach. This approach is powerful but has a problem with its potential huge search space. Using multiple cues we reduce the search space by introducing constraints through the 3D locations of salient points and a silhouette of the subject. Both data types are relatively easy to derive and only require limited computational effort so the approach remains suitable for real-time applications. The approach is tested on 3D movements of a human arm and the results show that we successfully can estimate the pose of the arm using the reduced search space.
Thomas B. Moeslund, Erik Granum
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where FGR
Authors Thomas B. Moeslund, Erik Granum
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