An Efficient Method of Shot Cut Detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
An Efficient Method of Shot Cut Detection

Authors: Lenka Krulikovská, Jaroslav Polec

Abstract:

In this paper we present a method of abrupt cut detection with a novel logic of frames- comparison. Actual frame is compared with its motion estimated prediction instead of comparison with successive frame. Four different similarity metrics were employed to estimate the resemblance of compared frames. Obtained results were evaluated by standard used measures of test accuracy and compared with existing approach. Based on the results, we claim the proposed method is more effective and Pearson correlation coefficient obtained the best results among chosen similarity metrics.

Keywords: Abrupt cut, mutual information, shot cut detection, Pearson correlation coefficient.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057479

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1880

References:


[1] Z. Cernekova, I. Pitas, and C. Nikou, "Information theory-based shot cut/fade detection and video summarization", IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no.1, page(s): 82- 91, January 2006
[2] A. Amiri and M. Fathy, "Video shot boundary detection using QR decomposition and Gaussian transition detection," EURASIP Journal on Advances in Signal Processing, Volume 2009, Article ID 509438.
[3] A. Hanjalic, "Shot-boundary detection: unraveled and resolved?," IEEE Transactions on Circuits and Systems for Video Technology, vol. 12, no. 2, pp. 90-105, 2002.
[4] J. S. Boreczky and L. A. Rowe, "Comparison of video shot boundary detection techniques," Storage and Retrieval for Still Image and Video Databases IV, Proc. SPIE 2664, pp. 170-179, 1996.
[5] R. Lienhart, "Comparison of automatic shot boundary detection algorithms," Storage and Retrieval for Image and Video Databases VII, vol. 3656 of Proceedings of SPIE, pp. 290-301, San Jose, Ca, USA, 1999.
[6] M. R. Naphade, R. Mehrotra, A. M. Ferman, J. Warnick, T. S. Huang and A. M. Tekalp, "A high-performance shot boundary detection algorithm using multiple cues," Proc. IEEE Int. Conf. on Image Proc., volume 2, pages 884-887, 1998.
[7] C. Taskiran and E. J. Delp, "Video scene change detection using the generalized sequence trace," Proc. IEEE Int. Conf. on Image Proc., pages 2961-2964, 1998.
[8] Y. Yusoff, J. Kittler and W. Christmas, "Combining multiple experts for classifying shot changes in video sequences," Proc. 6th Int. Conf. on Multimedia Comp. and Systems (ICMCS), volume 2, pages 700-704, Florence, Italy, 1999.
[9] R. Dugad, K. Ratakonda and N. Ahuja, "Robust video shot change detection", IEEE Workshop on Multimedia Signal Processing, 1998.
[10] B. L. Yeo and B. Liu, "Rapid scene analysis on compressed video," IEEE Trans. On Circuits and Systems for Video Technology, 5(6):533- 544, 1995.
[11] R. Zabih, J. Miller and K. Mai, "A feature-based algorithm for detecting and classifying production effects," ACM Multimedia Systems, 7(2):119-128, 1999.
[12] S. PASCHALAKIS and D. SIMMONS, (2008, April 24), "Detection of gradual transitions in video sequences" (Online]. Available: http://www.wipo.int/pctdb/en/wo.jsp?WO=2008046748&IA=EP200706 0594&DISPLAY=STATUS.
[13] S. CUMAR (22.10.2001), "An introduction to image compression" (Online). Available: http://www.debugmode.com/imagecmp/
[14] Y. K. Eugene, and R. G. Johnston, "The Ineffectiveness of the Correlation Coefficient for Image Comparisons," Technical Report LAUR- 96-2474, Los Alamos, 1996.