Fractal Dimension Based Shot Transition Detection in Sport Videos

Efnan Sora Gunal, Selcuk Canbek, Nihat Adar

.

DOI: 10.4236/jsea.2011.44026                

Abstract

Increase in application fields of video has boosted the demand to analyze and organize video libraries for efficient scene analysis and information retrieval. This paper addresses the detection of shot transitions, which plays a crucial role in scene analysis, using a novel method based on fractal dimension (FD) that carries information on roughness of image intensity surface and textural structure. The proposed method is tested on sport videos including soccer and tennis matches that contain considerable amount of abrupt and gradual shot transitions. Experimental results indicate that the FD based shot transition detection method offers promising performance with respect to pixel and histogram based methods available in the literature.

Keywords

Scene Analysis, Shot Transition, Fractal Dimension, Differential Box Counting

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	W. A. C. Fernando, C. N. Canagarajah and D. R. Bull, “A unified Approach to Scene Change Detection in Uncompressed and Compressed Video,” IEEE Transactions on Consumer Electronics, Vol. 46, No. 3, 2000, pp. 769-779. doi:10.1109/30.883445
[2]	W. A. C. Fernando, C. N. Canagarajah and D. R. Bull, “Scene Change Detection Algorithms for Content Based Video Indexing and Retrieval,” Electronics & Communication Engineering Journal, Vol. 13, No. 3, 2001, pp. 117-126. doi:10.1049/ecej:20010302
[3]	O. Marques and B. Furht, “Content-Based Image and Video Retrieval,” Kluwer Academic Publishers, Massachusetts, 2002.
[4]	J. Korpi-Anttilla, “Automatic Color Enhancement and Scene Change Detection of Digital Video,” Licentiate Thesis, Licentiate Thesis, Helsinki University of Technology, Finland, 2002.
[5]	H. Lu and Y. P. Tan, “An Effective Post-Refinement Method for Shot Boundary Detection,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 15, No. 11, 2005, pp. 1407-1421.
[6]	J. S. Boreczky and L. A. Rowe, “A Comparison of Video Shot Boundary Detection Techniques,” Journal of Electronic Imaging, Vol. 5, No. 2, 1996, pp. 122-128. doi:10.1117/12.238675
[7]	A. Ekin, “Sports Video Processing for Description, Summarization and Search,” PhD Thesis, University of Rochester, Rochester, 2003.
[8]	H. J. Zhang, A. Kankanhalli and S. W. Smoliar, “Automatic Partitioning of Full-Motion Video,” Multimedia Systems, Vol. 1, No. 1, 1993, pp. 10-28. doi:10.1007/BF01210504
[9]	B. Mandelbrot, “Fractals: Form, Change and Dimension,” Freeman, San Francisco, 1977.
[10]	Y. Liu and Y. Li, “Image Feature Extraction and Segmentation Using Fractal Dimension,” Proceedings of International Conference on Information, Communication and Signal Processing, Singapore, Vol. 2, 9-12 September 1997, pp. 975-979.
[11]	N. Sarkar and B. B. Chaudri, “An Efficient Differential Box-Counting Approach to Compute Fractal Dimension of Image,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 24, No. 1, 1994, pp. 115-120. doi:10.1109/21.259692
[12]	J. L. Véhel and P. Mignot, “Multifractal Segmentation of Images,” Fractals, Vol. 2, No. 3, 1994, pp. 371-377.
[13]	T. Sato, M. Matsuoka and H. Takayasu, “Fractal Image Analysis of Natural Scenes and Medical Images,” Fractals, Vol. 4, No. 4, 1996, pp. 463-468. doi:10.1142/S0218348X96000571
[14]	K. Revathy, G. Raju and S. R. Prabhakaran Nayar, “Image Zooming by Wavelets,” Fractals, Vol. 8, No. 3, 2000, pp. 247-253.
[15]	C. Hufnagl and A. Uhl, “Fractal Block-Matching in Motion-Compensated Video Coding,” Fractals, Vol. 8, No. 1, 2000, pp. 35-48.
[16]	V. Drakopoulos, P. Bouboulis and S. Theodoridis, “Image Compression Using Affine Fractal Interpolation on Rectangular Lattices,” Fractals, Vol. 14, No. 4, 2006, pp. 259-269. doi:10.1142/S0218348X06003271
[17]	Y. Fisher, “Fractal Image Compression,” Fractals, Vol. 2, No. 3, 1994, pp. 347-361. doi:10.1142/S0218348X94000442
[18]	N. H. Bach, K. Shinoda and S. Furui, “Robust Scene Extraction Using Multi-Stream HMMs for Baseball Broadcast,” IEICE Transactions on Information and Systems, Vol. E89-D, No. 9, 2006, pp. 2553-2561.
[19]	E. S. Gunal, S. Canbek and N. Adar, “Gradual Shot Change Detection in Soccer Videos via Fractals,” Proceedings of the 6th International Conference on Electrical and Electronics Engineering (ELECO'09), Bursa, 5-8 November 2009, pp.125-128.
[20]	E. S. Gunal, “Feature Extraction by Fractal Dimension in Pattern Recognition Applications,” PhD Thesis, Eskisehir Osmangazi University, Eskisehir, 2010.
[21]	A. Nagasaka and Y. Tanaka, “Automatic Video Indexing and Full-Video Search for Object Appearances,” Journal of Information Processing, Vol. 15, No. 2, 1992, p.316.
[22]	Y. Tonomura, “Video Handling Based on Structured Information for Hypermedia Systems,” Proceedings of International Conference on Multimedia Information Systems, Jurong, November 1991, pp. 333-344.
[23]	U. Gargi, R. Kasturi and S. H. Strayer, “Performance Characterization of Video-Shot-Change Detection Methods,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 10, No. 1, 2000, pp. 1-13. doi:10.1109/76.825852
[24]	M. J. Swain and D. H. Ballard, “Color Indexing,” International Journal of Computer Vision, Vol. 26, No. 4, 1993, pp. 461-470.
[25]	M. F. Barnsley, “Fractals Everywhere,” Academic Press, Boston, 1988.
[26]	B. B. Chaudhuri and N. Sarkar, “Texture Segmentation Using Fractal Dimension,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No. 1, pp. 72-77, 1995. doi:10.1109/34.368149
[27]	B. Gunsel and A. Murat Tekalp, “Content-Based Video Abstraction,” Proceedings of International Conference on Image Processing, Chicago, Vol. 3, 4-7 October 1998, pp. 128-122.
[28]	J. Meng, Y. Juan and S. F. Chang, “Scene Change Detection in a MPEG Compressed Video Sequence,” Proceedings of IS&T/SPIE International Symposium on Electronic Imaging, San Jose, Vol. 2419, February 1995, pp. 14-25.
[29]	X. Wang and Z. Weng, “Scene Abrupt Change Detection,” Canadian Conference on Electrical and Computer Engineering, Halifax, Vol. 2, 7-10 March 2000, pp. 880- 883.
[30]	S. Youm and W. Kim, “Dynamic Threshold Method for Scene Change Detection,” Proceedings of International Conference on Multimedia and Expo, Baltimore, Maryland, Vol. 2, July 2003, pp. 337-340.
[31]	C. D. Manning, P. Raghavan and H. Schütze, “Introduction to Information Retrieval,” Cambridge University Press, Cambridge, 2008.