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1 August 2008 Online optimal path decoder of hidden Markov model and its application to connected gesture recognition
Monalisa Mazumdar, Mun-Ho Jeong, Bum-Jae You
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Optical Engineering, Vol. 47, Issue 8, 087204 (August 2008). https://doi.org/10.1117/1.2969123
Abstract
We model a recognition problem for connected hand gestures to find an optimal path through a hidden Markov model (HMM) directed acyclic graph. To determine this optimal path, an online graph search method is proposed that decodes the observed gesture pattern and evaluates the optimal graph node at each time frame of the continuously deepening HMM graph. The temporal characteristic of gesture recognition is subsequently handled by introducing a rejection threshold time that acts as a depth-wise sliding window for pruning unnecessary graph nodes. The functional depth of the graph is defined by this depth rejection threshold. Experimental comparison of our algorithm with other HMM-based search algorithms demonstrates the effectiveness and robustness of our method.
©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
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Monalisa Mazumdar, Mun-Ho Jeong, and Bum-Jae You "Online optimal path decoder of hidden Markov model and its application to connected gesture recognition," Optical Engineering 47(8), 087204 (1 August 2008). https://doi.org/10.1117/1.2969123
Published: 1 August 2008
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KEYWORDS
Detection and tracking algorithms
Gesture recognition
Optical engineering
Computing systems
Visual process modeling
Algorithms
Cameras
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