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http://dx.doi.org/10.7236/JIWIT.2012.12.2.119

Implementation of a 3D Recognition applying Depth map and HMM  

Han, Chang-Ho (Dept. of Information and Communication Engineering, SunMoon University)
Oh, Choon-Suk (Dept. of Information and Communication Engineering, SunMoon University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.12, no.2, 2012 , pp. 119-126 More about this Journal
Abstract
Recently, we used to recognize for human motions with some recognition algorithms. examples, HMM, DTW, PCA etc. In many human motions, we concentrated our research on recognizing fighting motions. In previous work, to obtain the fighting motion data, we used motion capture system which is developed with some active markers and infrared rays cameras and 3 dimension information converting algorithms by the stereo matching method. In this paper, we describe that the different method to acquiring 3 dimension fighting motion data and a HMM algorithm to recognize the data. One of the obtaining 3d data we used is depth map algorithm which is calculated by a stereo method. We test the 3d acquiring and the motion recognition system, and show the results of accuracy and performance results.
Keywords
HMM; Disparity; Depth map; Stereo Vision; Recognition;
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1 Jean, Grace V. Road warriors: robots get smarter, but who will buy them? National Defense, March 2008.
2 Kageyama, Yuri. "Walking, talking female robot to hit Japan catwalk." The Seattle Times. 16 March 2009.
3 OPRoS 팀, www.opros.or.kr
4 Park,H.S., "Development of robot S/W platform verification and estimation automation technology", OPRoS combination workshop 2008. 11.
5 Han,C.H., Oh,C.S., "Development of a 3D Object Recognition Component for OPRoS", IWIT, Vol11-3-12, 2011. 6
6 Trucco, Emanuele. Introductory Techniques for 3D Computer Vision. Prentice Hall Inc, 1998.
7 H. Jeong and S.C. Park, "Generalized Trellis Stereo Matching with Systolic Array," In Lecture Notes in Computer Science, Vol.3358, 2004, pp.263-267.
8 Abhijit S. Ogale and Yiannis Aloimonos, "Shape and the Stereo Correspondence Problem", DCV 65,3, pp. 147- 162, 2005.
9 Sukjune Yoon, Sung-Kee Park, Sungchul Kang, Yoon Keun Kwak, "Fast correlation-based stereo matching with the reduction of systematic errors", Pattern Recognition Letters 26, pp. 2221- 2231,2005.   DOI
10 Michael Bleyer, Margrit Gelautz, "A layered stereo matching algorithm using image segmentation and global visibility constraints", ISPRS Journal of Photogrammetry & Remote Sensing 59, pp. 128- 150, 2005.   DOI
11 Hansung Kim, Kwanghoon Sohn, "3D reconstruction from stereo images for interactions between real and virtual objects", Signal Processing: Image Communication 20, pp. 61- 75, 2005.   DOI
12 K. Muhlmann, D. Maier, 1. Hesser and R. Manner, "Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation", DCV 47, 1/2/3, pp. 79-88, 2002.
13 Bradski, Gary; Kaehler, Adrian. Learning OpenCV: Computer Vision with the OpenCV Library. O'Reilly Media Inc, 2008.