On clustering and retrieval of video shots
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Video Clustering Using SuperHistograms in Large Archives
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
Motion-Location Based Indexing Method for Retrieving MPEG Videos
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Rapid estimation of camera motion from compressed video with application to video annotation
IEEE Transactions on Circuits and Systems for Video Technology
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
MPEG-7 visual motion descriptors
IEEE Transactions on Circuits and Systems for Video Technology
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Due to the tremendous growth in the number of digital videos, the development of video retrieval algorithms that can perform efficient and effective retrieval task is indispensable. In this paper, we propose a high-level motion-pattern descriptor, temporal motion intensity of moving blobs (MIMB) moments, which exploits spatial and temporal features to characterize video sequences in a semantics-based manner. The Discrete Cosine Transform (DCT) is applied to convert the high-level features from the time domain to the frequency domain. The energy concentration property of DCT allows us to use only a few DCT coefficients to precisely capture the variations of moving blobs. Compared to the motion activity descriptors, RLD and SAH in MPEG-7, the proposed descriptor yield 41% and 20% average performance gains over RLD and SAH, respectively. Having the efficient scheme for video representation, one can perform video retrieval in an accurate and efficient way.