Using mutual relationship between motion vectors for qualitative camera motion classification in MPEG video

Xiangyang Xue; Xingquan Zhu; Youneng Xiao; Lide Wu

doi:10.1117/12.477081

31 July 2002 Using mutual relationship between motion vectors for qualitative camera motion classification in MPEG video

Xiangyang Xue, Xingquan Zhu, Youneng Xiao, Lide Wu

Author Affiliations +

Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477081
Event: Second International Conference on Image and Graphics, 2002, Hefei, China

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.

Citation Download Citation

Xiangyang Xue, Xingquan Zhu, Youneng Xiao, and Lide Wu "Using mutual relationship between motion vectors for qualitative camera motion classification in MPEG video", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477081

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