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Reseach Article

Frame based Video Retrieval using Video Signatures

by Siva Kumar Avula, Shubhangi C Deshmukh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 10
Year of Publication: 2012
Authors: Siva Kumar Avula, Shubhangi C Deshmukh
10.5120/9586-4070

Siva Kumar Avula, Shubhangi C Deshmukh . Frame based Video Retrieval using Video Signatures. International Journal of Computer Applications. 59, 10 ( December 2012), 35-40. DOI=10.5120/9586-4070

@article{ 10.5120/9586-4070,
author = { Siva Kumar Avula, Shubhangi C Deshmukh },
title = { Frame based Video Retrieval using Video Signatures },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 10 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 35-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number10/9586-4070/ },
doi = { 10.5120/9586-4070 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:03:51.176615+05:30
%A Siva Kumar Avula
%A Shubhangi C Deshmukh
%T Frame based Video Retrieval using Video Signatures
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 10
%P 35-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The World Wide Web today has grown so wide and the video-on-demand applications and video share web are becoming very popular day-by-day on the World Wide Web. An efficient video similarity search algorithm for content-based video retrieval is important in video-on-demand based services. However, there is no satisfying video similarity search algorithm showing cent percentage performance. It is proposed here to implement a video similarity measure algorithm based on the color-features of each video represented by a compact fixed size representation known as Video Signature. This Video signature which is based on the image signature is computed on the basis of YCbCr Histogram and the sum of its weighted means. The video signatures of videos are then used to find the similar videos in-terms of visually similar frames, by using the range. This method of similarity measure is assumed to be efficient in various aspects.

References
  1. Jawahar. C. V. , Chennupati. B. , Paluri. B. , & Jammalamadaka. N. (2005, December). "Video Retrieval Based on Textual Queries". Proceedings of the Thirteenth International Conference on Advanced Computing and Communications .
  2. T. N. Shanmugam, & Rajendran, P. (2009). "An Enhanced Content-based Video Retrieval System based on Query Clip". International Journal of Research and Reviews in Applied Sciences, Volume 1, Issue 3.
  3. S, C. , & Zakhor. A. (2003). "Fast similarity search on video signatures". IEEE International Conference on Image Processing, Vol. 3.
  4. Sen-Cheung. S, & Zakhor, A. (2003). "Efficient video similarity measurement with video signature". IEEE Transactions on Circuits and Systems for Video Technology , Vol. 13.
  5. Cao, Z. , & Zhu, M. (2009). "An efficient video similarity search strategy for video-on-demand systems". 2nd IEEE International Conference on Broadband Network & Multimedia Technology, IC-BNMT '09 .
  6. P. Indyk and R. Motwani. Approximate Nearest Neighbor - Towards Removing the Curse of Dimensionality. In Proceedings of the 30th Symposium on Theory of Computing, 1998, pp. 604-613.
  7. Yu-Hsuan Ho, Chia-Wen Lin, Jing-Fung Chen et al. Fast Coarse-to-Fine Video Retrieval Using Shot-Level Spatio-Temporal Statistics. IEEE Trans. on Circuits and Systems for Video Technology, 2006 vol. 16, pp. 642-648
  8. H. T. Shen, X. Zhou, Z. Huang, and J. Shao. Statistical summarization of content features for fast near-duplicate video detection. Proc. of ACM int'l conf. on Multimedia, 2007 pp. 164–165
  9. Ma Y-F, Zhang H-J Motion Texture: A New Motion based Video Representation Proc. Of Int'l Conf. on Pattern Recognition, 2002 vol. 2 pp. 548-551
  10. Yan Ke Rahul Sukthankar Larry Huston An efficient parts-based near-duplicate and subimage retrieval system Proc. of the 12th annual ACM int'l conf. on Multimedia 2004 pp. 869-876
  11. Yang X, Tian Qi, Chang E-C A color fingerprint of video shot for content identificationin Proc. of the 12th annual ACM int'l conf. on Multimedia 2004 pp. 276-279
  12. Naturel X, Gros P Detecting repeats for video structuring Multimedia Tools and Applications 2008 vol. 38 pp. 233-252
  13. Radhakrishnan R, Bauer C Content-based Video Signatures based on Projections of Difference Images Proc. of IEEE 9th Workshop on Multimedia Signal Processing, 2007 pp. 341-344
  14. Gionis A, Indyk P, Motwani R Similarity search in high dimensions via hashing. Proc. of the 25th Int. Conf. on Very Large Data Bases 1999 pp. 518–529
Index Terms

Computer Science
Information Sciences

Keywords

YCbCr Video Signature