A Hybrid HMM/DPA Adaptive Gesture Recognition Method

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A Hybrid HMM/DPA Adaptive Gesture Recognition Method
We present a hybrid classification method applicable to gesture recognition. The method combines elements of Hidden Markov Models (HMM) and various Dynamic Programming Alignment (DPA) methods, such as edit distance, sequence alignment, and dynamic time warping. As opposed to existing approaches which treat HMM and DPA as either competing or complementing methods, we provide a common framework which allows us to combine ideas from both HMM and DPA research. The combined approach takes on the robustness and effectiveness of HMMs and the simplicity of DPA approaches. We have implemented and successfully tested the proposed algorithm on various gesture data.
Stjepan Rajko, Gang Qian
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where ISVC
Authors Stjepan Rajko, Gang Qian
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