A Comprhensive CBVR System Based on Spatiotemporal Features Such as Motion,Quantized Color and Edge Density Features
Автор: Kalpana S.Thakre, Archana M.Rajurkar
Журнал: International Journal of Wireless and Microwave Technologies(IJWMT) @ijwmt
Статья в выпуске: 3 Vol.1, 2011 года.
Бесплатный доступ
Rapid development of the multimedia and the associated technologies urge the processing of a huge database of video clips. The processing efficiency depends on the search methodologies utilized in the video processing system. Use of inappropriate search methodologies may make the processing system ineffective. Hence, an effective video retrieval system is an essential pre-requisite for searching relevant videos from a huge collection of videos. In this paper, an effective content based video retrieval system based on some dominant features such as motion, color and edge is proposed. The system is evaluated using the video clips of format MPEG-2 and then precision-recall is determined for the test clip.
Content based video retrieval (CBVR) system, shot segmentation, motion feature, quantized color feature, edge density, Latent Semantic Indexing (LSI)
Короткий адрес: https://sciup.org/15012736
IDR: 15012736
Список литературы A Comprhensive CBVR System Based on Spatiotemporal Features Such as Motion,Quantized Color and Edge Density Features
- Che-Yen Wen, Liang-Fan Chang and Hung-Hsin Li,"Content based video retrieval with motion vectors and the RGB color model", Forensic Science Journal, Vol.6,No.2, pp.1-36, 2007.
- Richard Hallows, “Techniques used in the content-based retrieval of digital video”, 2nd Annual CM316 Conference on Multimedia Systems, based at Southampton University,UK.
- T.N.Shanmugam and Priya Rajendran, “An Enhanced Content-Based Video Retrieval System Based On Query Clip”, ISSN: 2076-734X, EISSN: 2076-7366 Volume 1, Issue 3(December 2009).
- Chia-Hung Wei, Chang-Tsun Li, “Content–based multimedia retrieval - introduction, applications, design of content-based retrieval systems, feature extraction and representation”, 2004.
- Shih-Fu Chang, “Compressed-Domain Content-Based Image and Video retrieval”, Published in Symposium on Multimedia Communications and Video Coding, Polytechnic University, New York, Oct. 1995.
- Yong Rui, Thomas S. Huang, and Shih-Fu Chang, “Image Retrieval: Current Techniques, Promising Directions and Open Issues. Jan 7 1999.
- Aigrain, P., Zhang, H.J., Petkovic, D., “Content-Based Representation and Retrieval of Visual Media: A State-of-the-Art Review”, MultToolApp(3), No. 3, November 1996, pp. 179-202. 9611.
- M. J. Swain and D. H. Ballard, "Color Indexing”, International Journal of Computer Vision, Vol.7, pp.11 - 32, 1991.
- Lu G. & Phillips J. (1998), "Using perceptually weighted histograms for colour-based image retrieval", Proceedings of Fourth International Conference on Signal Processing, 12-16 October 1998, Beijing, China, pp. 1150-1153.
- Heng Tao Shen, Jie Shao, Zi Huang and Xiaofang Zhou, "Effective and Efficient Query Processing for Video Subsequence Identification", IEEE Transactions on Knowledge and Data Engineering, Vol.21, No.3, pp.321-334, March 2009.
