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.

• Type: Journal
• Year: 2010
• Where: ICPR
• Authors: Manavender R. Malgireddy, Jason J. Corso, Srirangaraj Setlur, Venu Govindaraju, Dinesh Mandalapu
• Keywords: Computer Vision, Gesture, Gesture Boundaries, ICPR 2010, Visual Features