In this paper, we propose motion pattern-based descriptor which exploits both 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. In comparison with the frequently used motion activity descriptors, the RLD and SAH of MPEG-7, the proposed descriptor yields 38% and 19 % average gains over RLD and SAH, respectively. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Chen, D. Y., Liao, H. Y. M., & Lee, S. Y. (2005). Robust video retrieval using temporal MVMB moments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3683 LNAI, pp. 359–365). Springer Verlag. https://doi.org/10.1007/11553939_52
Mendeley helps you to discover research relevant for your work.