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A Framework for Hand Gesture Recognition and Spotting Using Sub-gesture Modeling

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A Framework for Hand Gesture Recognition and Spotting Using Sub-gesture Modeling
Hand gesture interpretation is an open research problem in Human Computer Interaction (HCI), which involves locating gesture boundaries (Gesture Spotting) in a continuous video sequence and recognizing the gesture. Existing techniques model each gesture as a temporal sequence of visual features extracted from individual frames which is not efficient due to the large variability of frames at different timestamps. In this paper, we propose a new sub-gesture modeling approach which represents each gesture as a sequence of fixed sub-gestures (a group of consecutive frames with locally coherent context) and provides a robust modeling of the visual features. We further extend this approach to the task of gesture spotting where the gesture boundaries are identified using a filler model and gesturecompletion model. Experimental results show that the proposed method outperforms state-of-the-art Hidden Conditional Random Fields (HCRF) based methods and baseline gesture spotting techniques.
Manavender R. Malgireddy, Jason J. Corso, Sriranga
Added 04 Mar 2011
Updated 04 Mar 2011
Type Journal
Year 2010
Where ICPR
Authors Manavender R. Malgireddy, Jason J. Corso, Srirangaraj Setlur, Venu Govindaraju, Dinesh Mandalapu
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