Abstract
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.
This work is supported by the Ministry of Economic Affairs under contract no. 93-EC-17-A-02-S1-032
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Chen, DY., Liao, HY.M., Lee, SY. (2005). Robust Video Retrieval Using Temporal MVMB Moments. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_52
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DOI: https://doi.org/10.1007/11553939_52
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