single-jc.php

JACIII Vol.13 No.3 pp. 193-203
doi: 10.20965/jaciii.2009.p0193
(2009)

Paper:

Soccer Player’s Pose Recognition by Creative Search for Generating Free Viewpoint Images

Haruki Kawanaka*, Fuminori Matsubara**,
and Yuji Iwahori**

*School of Information Science & Technology, Aichi Prefectural University 1522-3 Ibaragabasama, Kumabari, Nagakute-cho, Aichi-gun, Aichi 480-1198, Japan

**Department of Computer Science, Chubu University 1200 Matsumoto-cho, Kasugai, Aichi 487-8501, Japan

Received:
November 25, 2008
Accepted:
February 9, 2009
Published:
May 20, 2009
Keywords:
pose recognition, parametric eigenspace method, principal component analysis, free viewpoint image
Abstract

The low-cost generation we have proposed for a free viewpoint image of soccer games uses a multiple viewpoint image database designed with computer graphics for recognizing player poses in the real image and for generating virtual scenes. A pose is recognized from a player’s silhouette and applying parametric eigenspace method. Because only silhouette information is used, however, limb positioning may be backward or the body misdirected. Our new proposal for excluding misplaced left and right limb poses assumes that changes in a pose, especially limb positioning, between sequential frames are continuous, so the limb positioning in 3D space and 2D images can be determined and the search range restricted in eigenspace. We also propose generating continuous frames for cases in which a correct pose exists outside of the restricted range by setting an initial state and handling error.

Cite this article as:
Haruki Kawanaka, Fuminori Matsubara, and
and Yuji Iwahori, “Soccer Player’s Pose Recognition by Creative Search for Generating Free Viewpoint Images,” J. Adv. Comput. Intell. Intell. Inform., Vol.13, No.3, pp. 193-203, 2009.
Data files:
References
  1. [1] M. Levoy and P. Hanrahan, “Light field rendering,” Proc. ACM SIGGRAPH 96, pp. 31-42, 1996.
  2. [2] T. Naemura, M. Kaneko, and H. Harashima, “Ray-based rendering for virtual light sources,” The Institute of Image Information and Television Engineers, pp. 1328-1335, 1998.
  3. [3] Y. Sato and K. Ikeuchi, “Temporal-color space analysis of reflection,” Journal of Optical Society of America, A, Vol.11, No.11, pp. 2990-3002, 1994.
  4. [4] K. Ikeuchi and Y. Sato, “Modeling from Reality,” Kluwer Academic Press, 2001.
  5. [5] K. Hayashi and H. Saito, “Synthesizing free-viewpoint images from multiple view videos in soccer stadium,” Int. Conf. on Computer Graphics, Imaging and Visualization, CGIV'06, pp. 220-225, 2006.
  6. [6] T. Koyama, I. Kitahara, and Y. Ohta, “Live mixed-reality 3d video in soccer stadium,” 2nd Int. Symposium on Mixed and Augmented Reality, ISMAR’03, pp. 178-187, 2003.
  7. [7] H. Kawanaka, N. Sado, and Y. Iwahori, “Generation of virtual image from multi-viewpoint image database,” Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems, KES2004, LNCS 3214, pp. 118-123, 2004.
  8. [8] H. Murase and S. K. Nayar, “Visual learning and recognition of 3-d objects from appearance,” Int. Journal of Computer Vision, Vol.14, No.1, pp. 5-24, 1995.
  9. [9] Y. Iwahori, H. Kawanaka, T. Takai, Y. Adachi, and H. Itoh, “Particle Filter Based Tracking of Moving Object from Image Sequence,” Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems, KES2006, LNCS 4252, pp. 401-408, 2006.
  10. [10] Y. Iwahori, S. Okada, H. Kawanaka, S. Fukui, and R. J. Woodham, “Particle Filter Based Tracking for Crossing of Targets with Similar Pattern,” IAPR Conf. on Machine Vision Applications, MVA2007, pp. 307-310, 2007.
  11. [11] Y. Iwahori, N. Enda, S. Fukui, H. Kawanaka, R. J. Woodham, and Y. Adachi, “Efficient Tracking with AdaBoost and Particle Filter under Complicated Background,” Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems, KES2008, LNCS 5178, pp. 887-894, 2008.
  12. [12] K. Pearson, “On Lines and Planes of Closest Fit to Systems of Points in Space,” Philosophical Magazine, Vol.2, No.6, pp. 559-572, 1901.
  13. [13] P. S. Revankar, P. K. Biswas, and S. N. Deshpande, “Efficient Object Recognition Using Parametric Eigenspace under Influence of Noise and Occlusion,” 9th ACIS Int. Conf. on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD’08, pp. 494-500, 2008.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 25, 2021