Affiliation:
1. Dalian Nationalities University
Abstract
This paper describes the techniques used in visual based hand gesture recognition systems. The study is discussed from three aspects: the two categories, the five components, and the methods of feature extraction of visual based hand gesture recognition systems. The two categories are 3D model based systems and appearance model based systems. The five components are image sequences capture, pre-processing, hand regions detection, feature extraction and gesture classification. The methods of feature extraction are Hidden Markov Model (HMM), Artificial Neural Networks (ANN), and Support Vector Machines (SVM). The main ideas of each technique are described in detail.
Publisher
Trans Tech Publications, Ltd.
Reference15 articles.
1. Y. Fang, K. Wang, J. Cheng, and H. Lu: A Real-Time Hand Gesture Recognition Method, IEEE International Conference on Multimedia and Expo, Beijing, China, pp.995-998 (2007).
2. D. Wormell, E. Foxlin: Advancements in 3d interactive devices for virtual environments, Proceedings of the Workshop on Virtual Environments, pp.47-56 (2003).
3. D. J. Sturman, D. Zeltzer: A Survey of glove-based Input, IEEE Computer Graphics and Applications, Vol. 14, pp.30-39 (1994).
4. V. Ganapathi, C. Plagemann, S. Thrun, D. Koller: Real time motion capture using a single time-of-flight camera, IEEE Conference on Computer Vision and Pattern Recognition, pp.755-762 (2010).
5. M. Caputo, K. Denker, B. Dums, G. Umlauf: 3D Hand Gesture Recognition Based on Sensor Fusion of Commodity Hardware, Mensch & Computer, pp.293-302 (2012).
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