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Pubmed for Handhelds

PUBMED FOR HANDHELDS

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  • Title: Model-based hand tracking using a hierarchical Bayesian filter.
    Author: Stenger B, Thayananthan A, Torr PH, Cipolla R.
    Journal: IEEE Trans Pattern Anal Mach Intell; 2006 Sep; 28(9):1372-84. PubMed ID: 16929725.
    Abstract:
    This paper sets out a tracking framework, which is applied to the recovery of three-dimensional hand motion from an image sequence. The method handles the issues of initialization, tracking, and recovery in a unified way. In a single input image with no prior information of the hand pose, the algorithm is equivalent to a hierarchical detection scheme, where unlikely pose candidates are rapidly discarded. In image sequences, a dynamic model is used to guide the search and approximate the optimal filtering equations. A dynamic model is given by transition probabilities between regions in parameter space and is learned from training data obtained by capturing articulated motion. The algorithm is evaluated on a number of image sequences, which include hand motion with self-occlusion in front of a cluttered background.
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