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Proceedings Paper

Using mutual relationship between motion vectors for qualitative camera motion classification in MPEG video
Author(s): Xiangyang Xue; Xingquan Zhu; Youneng Xiao; Lide Wu
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Paper Abstract

Extensive researches have been executed to extract the camera motion in videos by utilizing temporal slices, analyzing optical flow distribution, using transformation model, etc. However, these strategies fail to detect the camera rotation; furthermore, extracted optical flow or motion vectors may contain considerable noise or error, which significantly reduces the efficiency of these strategies. In this paper, the mutual relationship between motion vectors is utilized for qualitative camera motion classification. We first define four types ofmutual relationships (parallel, approach, diverging and rotation) between any two motion vectors, then, a 14-bins feature vector is constructed to characterize the statistical motion information for each P-frame. Based on different distribution modes ofthe motion feature vector, the qualitative camera motion classification is executed. In addition to detecting most common camera motions (pan, tilt, zoom, still), our method can also detect camera rotation. Experimental results demonstrate successful classification over different types of video collections.

Paper Details

Date Published: 31 July 2002
PDF: 8 pages
Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477081
Show Author Affiliations
Xiangyang Xue, Fudan Univ. (China)
Xingquan Zhu, Purdue Univ. (United States)
Youneng Xiao, Fudan Univ. (China)
Lide Wu, Fudan Univ. (China)

Published in SPIE Proceedings Vol. 4875:
Second International Conference on Image and Graphics
Wei Sui, Editor(s)

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