Journal of Integrative Natural Science (통합자연과학논문집)

The Basic Science Institute Chosun University (조선대학교 기초과학연구원)
권호 표지
DOI QR코드

DOI QR Code

Gesture Recognition Using Higher Correlation Feature Information and PCA

  • Kim, Jong-Min (Computer Science and Statistic Graduate School, Chosun University) ;
  • Lee, Kee-Jun (Department of Health Education & Information, Gwangju Health College)
  • Received : 2012.05.13
  • Accepted : 2012.06.24
  • Published : 2012.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

Keywords

References

  1. J.Aggarwal, Q. Cai, "Human Motion Analysis: A Review", Computer Vision and Image Understanding, Vol. 73, No. 3, pp. 428-440, 1999. https://doi.org/10.1006/cviu.1998.0744
  2. Chistopher Wren, Ail Azarbayejani, Trevor Draeerl, and Alex Pentland. Pfinder:Real-time tracking of the human body. In Photonics East, SPIE Proceedings Vol. 2615 Bellingham,WA,1995.SPIE.
  3. I. B. Ozer, T. Lu, and W. Wolf, "Design of arealtime gesture recognition system: high performance through algorithms and software," IEEE, Signal Processing Magazine, Vol. 22, No.3, pp. 57-64, 2005. https://doi.org/10.1109/MSP.2005.1425898
  4. R. Bowden, R. Mitchell and M. Sarhadi, "Non-Linear Statistical Models for the 3D Reconstruction of Human Pose and Motion from Monocular Image Sequences," Image and Vision Computing, Vol. 18, No. 9, pp. 729-737, 2000. https://doi.org/10.1016/S0262-8856(99)00076-1
  5. Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing 2/E," Prentice Hall, pp. 519-532, 2001.
  6. Liang Xiao, Zhihui Wei, and Huizhong Wu, "Robust Orientation Diffusion Via PCA Method and Application to Image Super-Resolution Reconstruction", Lecture Notes in Computer Science LNCS.4688 pp. 726-735, 2007.
  7. J.-M. Kim, M.-K. Song, "Three Dimensional Gesture Recognition Using PCA of Stereo Images and Modified Matching Algorithm", IEEE Fuzzy Systems and Knowledge Discovery Vol. 4, pp. 116-120, Oct. 2008.