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Abstract: In gesture and sign language video sequences, hand motion tends to be rapid, and hands frequently appear in front of each other or in front of the face. Thus, hand location is often ambiguous, and naive color-based hand tracking is insufficient. To improve tracking accuracy, some methods employ a prediction-update framework, but such methods require careful initialization of model parameters, and tend to drift and lose track in extended sequences. In this paper, a temporal filtering framework... (Update)
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BibTeX entry: (Update)
@misc{ -unknown,
title = "Unknown",
url = "citeseer.ist.psu.edu/717130.html" }
Citations (may not include all citations):406 Sequential Monte Carlo Methods in Practice (context) - Doucet, de Freitas et al. - 2001
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27 Probabilistic data association methods for tracking complex .. - Rasmussen, Hager - 2001
13 Recognizing Hand Gesture Using Motion Trajectories - Yang, Ahuja - 1999
9 Using Multiple Cues for Hand Tracking and Model Refinement - Lu, Metaxas et al. - 2003
6 Model-Based 3D Tracking of an Articulated Hand (context) - Stenger, Mendonca et al. - 2001
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3 Visual Hand Tracking Using Nonparametric Belief Propagation (context) - Sudderth, Mandel et al. - 2004
3 ECHO data set for Sign Language of the Netherlands (NGT (context) - Crasborn, van der Kooij et al. - 2004
http://www.bu.edu/asllrp/cd/cont-s3.html
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