Motion-based MPEG video summarization Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/wd375z43f

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  • A new, fully automated summarization algorithm of MPEG compressed videos is designed to address the challenge of content based video retrieval. This algorithm segments the MPEG stream motion vector magnitudes using a seed growing region technique. Following the spatial segmentation of each frame, an intra-frame class-merging operation is performed. The resulting spatio-temporal classification is filtered to extract the video sequence main objects. The gravity centers of the identified objects are computed in background and fixed references, and are used to estimate the parameters of a 2-order ARMA model which summarizes the motion. Experimental results verify the effectiveness of the proposed algorithm and emphasize the usefulness of the MPEG motion vectors for object motion estimation.
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