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Reseach Article

Video Shot Detection using Saliency Measure

by Amudha J, Radha D, Naresh Kumar P
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 2
Year of Publication: 2012
Authors: Amudha J, Radha D, Naresh Kumar P
10.5120/6751-8999

Amudha J, Radha D, Naresh Kumar P . Video Shot Detection using Saliency Measure. International Journal of Computer Applications. 45, 2 ( May 2012), 17-24. DOI=10.5120/6751-8999

@article{ 10.5120/6751-8999,
author = { Amudha J, Radha D, Naresh Kumar P },
title = { Video Shot Detection using Saliency Measure },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 2 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number2/6751-8999/ },
doi = { 10.5120/6751-8999 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:34.506783+05:30
%A Amudha J
%A Radha D
%A Naresh Kumar P
%T Video Shot Detection using Saliency Measure
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 2
%P 17-24
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Video shot boundary is an early stage of content based video analysis and is fundamental to any kind to of video application. The increased availability and usage of online digital video has created a need for automated video content analysis techniques. Major bottle neck that limits a wider use of digital video is the ability of quickly finding desired information from a huge database. Manual indexing and annotating the video material are both computationally expensive and time consuming. In this paper we design a novel approach for shot boundary detection using visual attention model by comparing the saliency measures. The approach is robust to a wide range of digital effects with low computational complexity

References
  1. Engine Mendi, Coskun Bayrak, "Shot Boundary Detection and key Frame Extraction using Salient Region Detection and Structural similarity", ACMSE'10, April 15-17, 2010, Oxford, MS ,USA.
  2. Amudha J, K. P. Soman and Vasanth K (2008) "Video Annotation. Using Saliency", International conference on Image processing. Computer vision and Pattern Recognition" Vol 1, pp. 191-195.
  3. Amudha J, K. P. Soman and Y. Kiran (2011), "Feature Selection in Top Down Visual Attention Model with WEKA", International Journal of Computer application, Foundation of Computer Sciences, USA, Vol. 24, No. 4, pp. 38-43
  4. A. Hampapur, R. Jain, and T. Weymouth, ''Digital video segmentation,'' Proc. ACM Multimedia 94, pp. 357–364, San Francisco, CA (1994).
  5. B. Shahraray, ''Scene change detection and content-based sampling of video sequences,'' in Digital Video Compression: Algorithms and Technologies, Proc. SPIE 2419, 2–13 (1995).
  6. H. J. Zhang, A. Kankanhalli, and S. W. Smoliar, ''Automatic partitioning of full-motion video,'' Multi-media Systems, 10–28, (1993).
  7. A. Nagasaka and Y. Tanaka, ''Automatic video indexing and full video search for object appearances,'' in Visual Database Systems II, E. Knuth and L. Wegner, Eds. , pp. 113–127, Elsevier Science Publishers (1992).
  8. H. Ueda, T. Miyatake, and S. Yoshizawa, ''IMPACT: an interactive natural-motion-picture dedicated multimedia authoring system,'' Proc. CHI. 1991, pp. 343–350 ACM, New York (1991).
  9. R. Zabih, J. Miller, and K. Mai, ''A feature-based algorithm for detecting and classifying scene breaks,'' Proc. ACM Multimedia 95, pp. 189–200, San Francisco, CA (1995).
  10. R. Kasturi and R. Jain, ''Dynamic vision,'' in Computer Vision: Principles, R. Kasturi and R. Jain, Eds. , IEEE Computer Society Press, Washington (1991).
  11. Shan Li, Moon-Chuen Lee, 2005. An improved sliding window method for shot change detection. Proceeding of the 7th IASTED International Conference Signal and Image Processing, Aug. 15-17, IIonolulu, IIawaii, USA, pp: 464-468
  12. Cernekova. Z, N. Nikolaidis and I. Pitas, 2006. Temporal video segmentation by graph partitioning. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, May 14-19, 2: 209-212, Doi: 10. 1109/ ICASSP. 2006.
  13. R. Kasturi and R. Jain, Dynamic Vision, Computer Vision: Principles, R Kasturi and R. Jain (Eds. ), IEEE Computer Society Press, Washington DC, 1991, pp. 469-480.
  14. Edmundo Saez, José I. Benavides, Nicolas Guil, "Combining Luminance and Edge based Metrics for Robust Temporal Video segmentation", International Conference on Image Processing (ICIP), IEEE 2004.
  15. Jian Zhou, Xiao-Ping Zhang, "Video Shot Boundary Detection Using Independent Component Analysis", IEEE 2005
  16. Gao X. and Tang. X , 2002. Unsupervised video shot segmentation and model-free anchorperson detection for news video story parsing. IEEE Trans. Circuits Syst. Video Technol. , 12: pp. 765-776
  17. Gao X. and X. Tang, 2000. Automatic parsing of news video based on cluster analysis. In Proceedings of 2000 Asia Pacific Conference on Multimedia Technology and applications, Kaohsiung, Taiwai, China, Dec. 17-19, pp: 17-19.
  18. Han Bing, Gao Xin-bo, Ji Hong-bing, 2003. An efficient algorithm of gradual transition for shot boundary segmentation. 3rd International Symposium on Multispectral Image Processing and Pattern recognition (MIPPR'03), Beijing, 9:956-961.
  19. Alper YILMAZ, Mubarak Ali Shah, "Shot Detection Using Principal Coordinate System" University of Central Florida, USA, 2010.
  20. Nithya Manickam, Neela Sawant, Aman Parnami, Srikanth. L. , Sarath chandran, "TRECVID 2006", Indian Institute of Technology, Bombay.
  21. Ali Amiri and Mahmood Fathy, "VideoShot Detection Using QR-ecomposition and Gaussian Transition Detection", EURASIP journal on Advances in Signal Processing, Volume 2009, Article ID 509438, doi:10. 1155/2009/509438.
Index Terms

Computer Science
Information Sciences

Keywords

Shot Detection Saliency Measure And Visual Attention Model