Non-Parametric Motion Activity Analysis for Statistical Retrieval with Partial Query
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Shot Classification of Sports Video Based on Features in Motion Vector Field
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Proceedings of the 15th international conference on Multimedia
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EURASIP Journal on Advances in Signal Processing
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COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
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ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
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Multimedia Tools and Applications
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Journal of Visual Communication and Image Representation
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This paper describes an original approach to partitioning of a video document into shots. Instead of an interframe similarity measure which is directly intensity based, we exploit image motion information, which is generally more intrinsic to the video structure itself. The proposed scheme aims at detecting all types of transitions between shots using a single technique and the same parameter set, rather than a set of dedicated methods. The proposed shot change detection method is related to the computation, at each time instant, of the dominant image motion represented by a two-dimensional affine model. More precisely, we analyze the temporal evolution of the size of the support associated to the estimated dominant motion. Besides, the computation of the global motion model supplies by-products, such as qualitative camera motion description, which we describe in this paper, and other possible extensions, such as mosaicing and mobile zone detection. Results on videos of various content types are reported and validate the proposed approach