Abstract
Network cameras are becoming increasingly popular as surveillance devices. They compress the captured live video data into Motion JPEG and/or MPEG standard formats, and they transmit them through the IP network. MPEG-coded videos contain motion vectors that are useful information for video analysis. However, the motion vectors occurring in homogeneous, low-textured, and line regions tend to be unstable and noisy. To address this problem, the noisy motion vector elimination using vector-based zero comparison and global motion estimation was proposed. In this paper, we extend the existing elimination method by introducing a novel bi-directional vector-based zero comparison to enhance the accuracy of noisy motion vector elimination, and we propose an efficient algorithm for zero comparison. We demonstrate the effectiveness of the proposed method through several experiments using actual video data acquired by an MPEG video camera.
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References
Lie, W.N., Chen, R.L.: Tracking moving objects in mpeg-compressed videos. In: IEEE International Conference on Multimedia and Expo, ICME 2001, August 22-25, pp. 965–968 (2001)
Khan, J.I., Guo, Z., Oh, W.: Motion based object tracking in mpeg-2 stream for perceptual region discriminating rate transcoding. In: MULTIMEDIA 2001: Proceedings of the ninth ACM international conference on Multimedia, pp. 572–576. ACM, New York (2001)
Eng, H.L., Ma, K.K.: Motion trajectory extraction based on macroblock motion vectors for video indexing. In: Proceedings of International Conference on Image Processing, ICIP 1999, vol. 3, pp. 284–288 (1999)
Achanta, R., Kankanhalli, M., Mulhem, P.: Compressed domain object tracking for automatic indexing of objects in mpeg home video. In: Proceedings of IEEE International Conference on Multimedia and Expo, ICME 2002, vol. 2, pp. 61–64 (2002)
Favalli, L., Mecocci, A., Moschetti, F.: Object tracking for retrieval applications in mpeg-2. IEEE Transactions on Circuits and Systems for Video Technology 10, 427–432 (2000)
Colace, F., De Santo, M., Molinara, M., Percannella, G.: Noisy motion vectors removal for reliable camera parameters estimation in mpeg coded videos. In: Proceedings of International Conference on Information Technology: Research and Education, ITRE 2003, pp. 568–572 (2003)
Hesseler, W., Eickeler, S.: Mpeg-2 compressed-domain algorithms . EURASIP J. Appl. Signal Process 2006, 186–186 (2006)
Eng, H.L., Ma, K.K.: Motion trajectory extraction based on macroblock motion vectors for video indexing. In: Proceedings of International Conference on Image Processing, ICIP 1999, vol. 3, pp. 284–288 (1999)
Yokoyama, T., Ota, S., Watanabe, T.: Noisy mpeg motion vector reduction for motion analysis. In: AVSS 2009: Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 274–279 (2009)
Su, Y., Sun, M.T., Hsu, V.: Global motion estimation from coarsely sampled motion vector field and the applications. IEEE Trans. Circuits Syst. Video Techn. 15, 232–242 (2005)
Morita, T.: Motion detection and tracking based on local correlation matching. Transactions of the Institute of Electronics, Information and Communication Engineers, D-II J84-D-II 299–309 (2001) (in Japanese)
Iwasaki, T., Yokoyama, T., Watanabe, T., Koga, H.: Motion object detection and tracking using mpeg motion vectors in the compressed domain. IEICE Transactions on Information and Systems 91, 1592–1603 (2008) (in Japanese)
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Yokoyama, T., Watanabe, T. (2011). Noisy Motion Vector Elimination by Bi-directional Vector-Based Zero Comparison. In: Koch, R., Huang, F. (eds) Computer Vision – ACCV 2010 Workshops. ACCV 2010. Lecture Notes in Computer Science, vol 6468. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22822-3_11
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DOI: https://doi.org/10.1007/978-3-642-22822-3_11
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