Abstract
Motion information represents semantic conception in video to a certain extent. In this paper, according to coding characteristics of MPEG, a global-motion analysis method via rough-set-based video pre-classification is proposed. First, abnormal data in MPEG stream are removed. Then, condition attributes are extracted and samples are classified with rough set to obtain global-motion frames. Finally, their motion models are built up. So the method can overcome disturbance of local motion and promote veracity of estimations for six-parameter global motion model. Experiments show that it can veraciously distinguish global and non-global motions.
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Dufaux, F., Konrad, J.: Efficient, Robust, and Fast Global Motion Estimation for Video Coding. IEEE Trans. on Image Process. 9, 497–501 (2000)
Giunta, G., Mascia, U.: Estimation of Global Motion Parameters by Complex Linear Regression. IEEE Trans. on Image Process. 8, 1652–1657 (1999)
Yoo, K.Y., Kim, J.K.: A New Fast Local Motion Estimation Algorithm Using Global Motion. Signal Processing 68, 219–224 (1998)
Tan, Y.P., Saur, D.D., Kulkarni, S.R., Ramadge, P.J.: Rapid Estimation of Camera Motion from Compressed Video with Application to Video Annotation. IEEE Tans. on Circuits Syst. Video Techo. 10, 133–145 (2000)
Yu, T.L., Zhang, S.J.: Video Retrieval Based on the Global Motion Information. Acta Electronica Sinica 29, 1794–1798 (2001)
Pawlak, Z., Grzymala-Busse, J., Slowinski, R.: Rough Sets. Communications of the ACM 38, 89–95 (1995)
Wang, G.Y., Zhao, J., An, J.J., Wu, Y.: Theoretical Study on Attribute Reduction of Rough Set Theory: in Algebra View and Information View. In: Third International Conference on Cognitive Informatics, pp. 148–155 (2004)
Sudhir, G., Lee, J.C.M.: Video Annotation by Motion Interpretation Using Optical Flow Streams. Journal of Visual Communication and Image Representation 7, 354–368 (1996)
Divakaran, A., Sun, H.: Descriptor for Spatial Distribution of Motion Activity for Compressed Video. In: SPIE, vol. 2972, pp. 392–398 (2000)
Ma, Y.F., Zhang, H.J.: Motion Pattern Based Video Classification and Retrieval. EURASIP JASP 2, 199–208 (2003)
Wang, G.Y., Zheng, Z., Zhang, Y.: RIDAS– A Rough Set Based Intelligent Data Analysis System. In: Proceedings of the First Int. Conf. on Machine Learning and Cybernetics, pp. 646–649 (2002)
Wang, G.Y., Liu, F., Wu, Y.: Generating Rules and Reasoning under Inconsistencies. In: Proceedings of IEEE Intl. Conf. on Industrial Electronics, Control and Instrumentation, pp. 646–649 (2000)
Yin, D.S., Wang, G.Y., Wu, Y.: A Self-learning Algorithm for Decision Tree Pre-pruning. In: Proceedings of the Third International Conference on Machine Learning and Cybernetics, pp. 2140–2145 (2004)
Chapelle, O., Haffner, P., Vapnik, V.N.: Support Vector Machines for Histogram-Based Image Classification. IEEE Trans. On Neural Networks 10 (1999)
Lee, S.H., Bae, S.J., Park, H.J.: A Compact Radix –64 54*54 CMOS Redundant Binary Parallel Multiplier. IEICE Trans. ELENCTRON (2002)
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© 2005 Springer-Verlag Berlin Heidelberg
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Yuan, Z., Wu, Y., Wang, G., Li, J. (2005). A Global-Motion Analysis Method via Rough-Set-Based Video Pre-classification. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_34
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DOI: https://doi.org/10.1007/11548706_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28660-8
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