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Proceedings Paper

Motion-based segmentation scheme for feature extraction of hand gestures
Author(s): Yuanxin Zhu; Yu Huang; Guang-you Xu; Chih-Ho Yu
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Paper Abstract

The key motivation for visual interpretation of hand gestures is to introduce this natural and intuitive communication mode to human computer interaction. Visual interpretation of hand gesture had typically made use of high-level parametric models representing the body parts such as arms, figures, palms etc. and their connections to each other. Such 3D model-based interpretation has been successful in some case; however, heavy computation makes this approach a very difficult task. By use of variable- order parameterized models of image motion and robust dominant motion regression, in this paper, we propose a motion-based segmentation scheme to feature extraction of hand gestures. The proposed scheme can directly estimate image motion of an object in two unsegmented images and obtain fine segmentation of that object from background at the same time. Based on inter-frame image motion parameters and the fine segmentation, we can construct various motion features, shape features, or their combinations for the purpose of hand gesture interpretation. With these features 12 kind of hand gestures used in our experiment can be reliably interpreted.

Paper Details

Date Published: 25 September 1998
PDF: 4 pages
Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); doi: 10.1117/12.323643
Show Author Affiliations
Yuanxin Zhu, Tsinghua Univ. (China)
Yu Huang, Tsinghua Univ. (China)
Guang-you Xu, Tsinghua Univ. (China)
Chih-Ho Yu, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 3545:
International Symposium on Multispectral Image Processing (ISMIP'98)
Ji Zhou; Anil K. Jain; Tianxu Zhang; Yaoting Zhu; Mingyue Ding; Jianguo Liu, Editor(s)

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