Saliency-based video segmentation with graph cuts and sequentially updated priors

Authors:
Ken Fukuchi;Kouji Miyazato;Akisato Kimura;Shigeru Takagi;Junji Yamato
Affiliations:
Department of Information and Communication Systems Engineering, Okinawa National College of Technology, Japan;Department of Information and Communication Systems Engineering, Okinawa National College of Technology, Japan;NTT Communication Science Laboratories, NTT Corporation, Japan;Department of Information and Communication Systems Engineering, Okinawa National College of Technology, Japan;NTT Communication Science Laboratories, NTT Corporation, Japan
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

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Abstract

This paper proposes a new method for achieving precise video segmentation without any supervision or interaction. The main contributions of this report include 1) the introduction of fully automatic segmentation based on the maximum a posteriori (MAP) estimation of the Markov random field (MRF) with graph cuts and saliency-driven priors and 2) the updating of priors and feature likelihoods by integrating the previous segmentation results and the currently estimated saliency-based visual attention. Test results indicate that our new method precisely extracts probable regions from videos without any supervised interactions.