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http://dx.doi.org/10.5762/KAIS.2013.14.8.3971

Hand Movement Tracking and Recognizing Hand Gestures  

Park, Kwang-Chae (Electronic Engineering, Chosun University)
Bae, Ceol-Soo (Information and Communication Engineering, Kwandong University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.14, no.8, 2013 , pp. 3971-3975 More about this Journal
Abstract
This paper introduces an Augmented Reality system recognizing hand gestures and shows results of the evaluation. The system's user can interact with artificial objects and manipulate their position and motions simply by his hand gestures. Hand gesture recognition is based on Histograms of Oriented Gradients (HOG). Salient features of human hand appearance are detected by HOG blocks. Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification multiclass AdaBoostSVM algorithm is applied. Evaluated recognition rate of the algorithm is 94.0%.
Keywords
Augmented Reality; Hand Gesture Recognition; Histograms of Oriented Gradients;
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  • Reference
1 Hiroyuki Arai, "Measurement of mobile antenna systems," Artech House, 2001.
2 Gary E. Evans, "Antenna measurement techniques," Artech House, 1990.
3 N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection", Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1063-6919, 2005.
4 Robert E. Schapire and Yoram Singer, "Improved boosting algorithms using confidence-rated predictions," Machine Learning, vol. 37, no. 3, pp. 297-336, Dec 1999.   DOI   ScienceOn
5 V. Vapnik, S. Golowich, and A. Smola. "Support vector method for function approximation, regression estimation, and signal processing", In M. Mozer, M. Jordan, and T. Petsche, editors, Proc. Advances in Neural Information Processing Systems 9, pp. 281- 287, Cambridge, MA, 1997. MIT Press.
6 Zhu, Q.; Avidan, S.; Yeh, M-C; Cheng, K-W, "Fast Human Detection Using a Cascade of Histograms of Oriented Gradients", Proc. IEEE Computer Society Conference on Computer vision and Pattern Recognition, ISSN: 1063-6919, vol. 2, pp. 1491-1498, June 2006.
7 G. D. Abowd et. al., "Teaching and Learning as Multimedia Authoring: The Classroom 2000 Project," ACM Multimedia, pp. 187-198, 2000.
8 S. G. Deshpande & J.-N. Hwang, "A Real-time Interactive Virtual Classroom Multimedia Distance Learning System," IEEE Trans on Multimedia, vol. 3, no. 4, pp. 432-444, 2001.   DOI   ScienceOn
9 D. Phung, S. Venkatesh & C. Dorai, "High Level Segmentation of Instructional Videos Based on Content Density," ACM Multimedia, 2002.
10 Q. Liu, Y. Rui, A. Gupta & J. J. Cadiz, "Automatic Camera Management for Lecture Room Environment," Int. Conf. on Human Fectirs in Computing Systems, 2001.
11 T. F. S. -Mahmood, "Indexing for topics in videos using foils," Int. Conf. CVPR, pp. 312-319, 2000.
12 J. Martin & J. B. Durand, "Automatic Gestures Recognition Using Hidden Markov Models," Int. Conf. Automatic Face and Gesture Recognition, 2000.
13 C. W. Ngo, T. C. Pong & T. S. Huang, "Detection of Slide Transition for Topic Indexing," Int. Conf. on Multimedia Expo, 2002.