Head Detection and Localization from Sparse 3D Data
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Implicit Meshes for Effective Silhouette Handling
International Journal of Computer Vision
Recognizing and interpreting gestures on a mobile robot
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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In this paper we describe our work on 3-D model-based tracking of unconstrained human upper body movement. Using real image sequences acquired from multiple views, we recover the 3-D body pose at each time instant without the use of markers. The pose-recovery problem is formulated as a search problem and entails finding the pose parameters of a graphical human model for which its synthesized appearance is most similar to the actual appearance of the real human in the multi-view images. We use a decomposition approach and a best-first technique to search through the high dimensional pose parameter space. Chamfer matching is used as a fast similarity measure between synthesized and real edge images. We illustrate our approach on real data acquired simultaneously from three views.