Advanced SearchSearch Tips
A new approach for content-based video retrieval
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A new approach for content-based video retrieval
Kim, Nac-Woo; Lee, Byung-Tak; Koh, Jai-Sang; Song, Ho-Young;
  PDF(new window)
In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.
motion classification;representative frame;video retrieval;non-parametric;
 Cited by
N.W. Kim, E.K. Kang, et al., “Scene change detection and classification algorithm on compressed video streams,” Proc. of the ITC-CSCC 2001, vol. 1, 2001, pp. 279-282.

R. Wang R., T. Huang, “Fast camera motion analysis in MPEG domain,” International Conference on Image Processing, vol. 3, 1999, pp. 691-694.

N.W. Kim, T.Y. Kim, and J.S. Choi, “Probability-based motion analysis using bi-directional prediction-independent framework in compressed domain,” Optical engineering, vol. 44, no. 6, 067008.1-067008.13, 2005. crossref(new window)

Y. Deng, C. Kenney, M.S. Moore, and B.S. Manjunath, "Peer group filtering and perceptual color image quantization," Proc. of IEEE Intl. Symposium on Circuits and Systems, vol. 4, 1999, pp. 21-24.. crossref(new window)

N.W. Kim, T.Y. Kim, and J.S. Choi, “Edge-based spatial descriptor using color vector angle for effective image retrieval,” LNAI, vol. 3558, 2005, pp. 365-375.

J. Huang, S. R. Kumar, M. Mitra, W. J. Zhu, and R. Zabih, “Image indexing using color correlograms,” CVPR, 1997, pp. 762-768.

G. Pass and R. Zabih, "Histogram refinement for content-based image retrieval," IEEE WACV, 1996, pp. 96-102. crossref(new window)