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17 January 2005 Video summarization with moving objects in the compressed domain
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The vast amount of video sequences available in digital format presents considerable challenges for descriptor extraction and information retrieval. The dominant motion in a video scene proves to be very important to characterize video sequences, but the cost to compute it is high when working in image domain because the retrieval of the optical flow of two consecutive frames is very demanding in terms of time, as well as the following estimation of parameters. In this paper we present a method to extract an affine description of the global motion of a video sequence using a robust estimator based on compressed domain data, where the motion vector field is already calculated. We perform further analysis, isolating and describing parametrically the local motions using the mean shift analysis as non parametric clustering method. Applying our approach to real sequences, we take advantage of the parametric description extracted to perform video summarization of the sequences using image mosaics.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ramon Ll. Felip, Juan M. Sanchez, and Xavier Binefa "Video summarization with moving objects in the compressed domain", Proc. SPIE 5670, Internet Imaging VI, (17 January 2005);

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