An efficient compressed domain moving object segmentation algorithm based on motion vector field
In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated b...
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| Published in | Journal of Shanghai University Vol. 12; no. 3; pp. 221 - 227 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Heidelberg
Shanghai University Press
01.06.2008
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1007-6417 1863-236X |
| DOI | 10.1007/s11741-008-0307-2 |
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| Abstract | In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance. |
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| AbstractList | In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector (MV) field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance. In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance. |
| Author | 刘志 沈礼权 张兆杨 |
| AuthorAffiliation | School of Communication and Information Engineering, Shanghai University, Shanghai 200072, P. R. China Key Laboratory of Advanced Display and System Application of the Ministry of Education, Shanghai 200072, P. R. China |
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| Keywords | compressed domain segmentation motion vector (MV) field moving object segmentation |
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| References | Venkatesh, Ramakrishnan, Srinivasan (CR2) 2004; 14 Wiegand, Sullivan, Bjontegaard (CR9) 2003; 13 Mezaris, Kompatsiaris, Boulgouris (CR3) 2004; 14 Liu, Xu, Lu (CR11) 2006; 11 Jamrozik, Hayes (CR6) 2002; 1 Liu, Liu, Liu (CR8) 2004; 38 Zeng, Du, Gao (CR10) 2005; 11 Liu, Shen, Zhang (CR7) 2006; 1 Nock, Nielsen (CR12) 2005; 38 Press, Flannery, Teukolsky (CR13) 1992 Sukmarg, Rao (CR1) 2000; 3 Eng, Ma (CR4) 2000 Porikli (CR5) 2004; 5297 B. R. Venkatesh (307_CR2) 2004; 14 M. L. Jamrozik (307_CR6) 2002; 1 R. Nock (307_CR12) 2005; 38 L. Liu (307_CR8) 2004; 38 H. L. Eng (307_CR4) 2000 O. Sukmarg (307_CR1) 2000; 3 V. Mezaris (307_CR3) 2004; 14 Z. Liu (307_CR11) 2006; 11 W. Zeng (307_CR10) 2005; 11 W. H. Press (307_CR13) 1992 F. Porikli (307_CR5) 2004; 5297 Z. Liu (307_CR7) 2006; 1 T. Wiegand (307_CR9) 2003; 13 |
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| SubjectTerms | Classical Mechanics Engineering Environment Life Sciences Materials Science Mathematical and Computational Engineering Mechatronics 分割算法 压缩域 运动对象 运动矢量场 |
| Title | An efficient compressed domain moving object segmentation algorithm based on motion vector field |
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