A Real Time Hand Gesture Recognition System Based on DFT and SVM

Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.

[1]  Thomas Burger,et al.  Cued speech hand gestures recognition tool , 2005, 2005 13th European Signal Processing Conference.

[2]  Vladimir Pavlovic,et al.  Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  고성제,et al.  인터액티브 가상 환경을 위한 손 제스처 인식 시스템 ( A Hand Gesture Recognition System for Interactive Virtual Environment ) , 1999 .

[4]  Vladimir Pavlovic,et al.  Hand Gesture Modeling, Analysis, and Synthesis , 1995 .

[5]  Fengming Zhang,et al.  Hand Gesture Recognition Based on MEB-SVM , 2009, 2009 International Conference on Embedded Software and Systems.

[6]  Bruce A. Draper,et al.  Color Recognition by Learning: ATR in Color Images , 1997, BMVC.

[7]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[8]  Wu-Chih Hu,et al.  Vision-Based Hand Gesture Recognition Using PCA+Gabor Filters and SVM , 2009, 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[9]  Mu-Chun Su,et al.  A NEURAL-NETWORK-BASED APPROACH TO RECOGNIZING 3D ARM MOVEMENTS , 2003 .

[10]  Hiroaki Nishino,et al.  A virtual environment for modeling 3D objects through spatial interaction , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[11]  Shaofeng Liu,et al.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2006 .

[12]  Yen-Ting Chen,et al.  Multiple-angle Hand Gesture Recognition by Fusing SVM Classifiers , 2007, 2007 IEEE International Conference on Automation Science and Engineering.

[13]  Zhenyang Wu,et al.  Face Tracking Algorithm Based on Mean Shift and Ellipse Fitting , 2006, ICONIP.

[14]  Bian Wu,et al.  A hand gesture recognition system based on local linear embedding , 2005, J. Vis. Lang. Comput..

[15]  Kuan-Yu Chen,et al.  An integrated color and hand gesture recognition approach for an autonomous mobile robot , 2010, 2010 3rd International Congress on Image and Signal Processing.

[16]  Tsutomu Miyasato,et al.  New Image/Video Media and It's Application. An Interface System Based on Hand Gestures and Verbal Expressions for 3-D Shape Generation. , 1996 .

[17]  Gary Bradski,et al.  Computer Vision Face Tracking For Use in a Perceptual User Interface , 1998 .

[18]  JongShill Lee,et al.  Hand region extraction and gesture recognition from video stream with complex background through entropy analysis , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.