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2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Vision-Based Hand Gesture Recognition Using Combinational Features
Darmstadt, Germany
October 15-October 17
ISBN: 978-0-7695-4222-5
| ASCII Text | x | ||
| Chenglong Yu, Xuan Wang, Hejiao Huang, Jianping Shen, Kun Wu, "Vision-Based Hand Gesture Recognition Using Combinational Features," Intelligent Information Hiding and Multimedia Signal Processing, International Conference on, pp. 543-546, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/IIHMSP.2010.138, author = {Chenglong Yu and Xuan Wang and Hejiao Huang and Jianping Shen and Kun Wu}, title = {Vision-Based Hand Gesture Recognition Using Combinational Features}, journal ={Intelligent Information Hiding and Multimedia Signal Processing, International Conference on}, volume = {0}, year = {2010}, isbn = {978-0-7695-4222-5}, pages = {543-546}, doi = {http://doi.ieeecomputersociety.org/10.1109/IIHMSP.2010.138}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Intelligent Information Hiding and Multimedia Signal Processing, International Conference on TI - Vision-Based Hand Gesture Recognition Using Combinational Features SN - 978-0-7695-4222-5 SP543 EP546 A1 - Chenglong Yu, A1 - Xuan Wang, A1 - Hejiao Huang, A1 - Jianping Shen, A1 - Kun Wu, PY - 2010 KW - Hand gesture recognition KW - Combinational Feature Extraction KW - Multi-layer Perceptron VL - 0 JA - Intelligent Information Hiding and Multimedia Signal Processing, International Conference on ER - | |||
This paper presents a feature extraction method for hand gesture based on multi-layer perceptron. The feature of hand skin color in the YCbCr color space is used to detect hand gesture. The hand silhouette and features can be accurately extracted in means of binarizing the hand image and enhancing the contrast. Median and smoothing filters are integrated to remove the noise. Combinational parameters of Hu invariant moment, hand gesture region, and Fourier descriptor are created to form a new feature vector which can recognize hand gesture. To confirm the robustness of this proposed method, a dataset including 3500 images is built. Experimental results demonstrate that our system can successfully recognize hand gesture with 97.4% recognition rate.
Index Terms:
Hand gesture recognition, Combinational Feature Extraction, Multi-layer Perceptron
Citation:
Chenglong Yu, Xuan Wang, Hejiao Huang, Jianping Shen, Kun Wu, "Vision-Based Hand Gesture Recognition Using Combinational Features," iih-msp, pp.543-546, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2010
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