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Proceedings Paper

Video summarization with moving objects in the compressed domain
Author(s): Ramon Ll. Felip; Juan M. Sanchez; Xavier Binefa
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Paper Abstract

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.

Paper Details

Date Published: 17 January 2005
PDF: 12 pages
Proc. SPIE 5670, Internet Imaging VI, (17 January 2005); doi: 10.1117/12.587524
Show Author Affiliations
Ramon Ll. Felip, Univ. Autonoma de Barcelona (Spain)
Juan M. Sanchez, Visual Century Research S.L. (Spain)
Xavier Binefa, Univ. Autonoma de Barcelona (Spain)


Published in SPIE Proceedings Vol. 5670:
Internet Imaging VI
Simone Santini; Raimondo Schettini; Theo Gevers, Editor(s)

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