Object segmentation in videos from moving camera with MRFs on color and motion features

Authors:
Rita Cucchiara;Andrea Prati;Roberto Vezzani
Affiliations:
D.I.I.- University of Modena and Reggio Emilia, Modena, Italy;D.I.I.- University of Modena and Reggio Emilia, Modena, Italy;D.I.I.- University of Modena and Reggio Emilia, Modena, Italy
Venue:
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Year:
2003

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Abstract

In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based on a color segmentation followed by a region-merging on motion through Markov Random Fields (MRFs). The technique we propose is inspired to a work of Gelgon and Bouthemy [6], that has been modified to reduce computational cost in order to achieve a fast segmentation (about ten frame per second). To this aim a modified region matching algorithm (namely Partitioned Region Matching) and an innovative arc-based MRF optimization algorithm with a suitable definition of the motion reliability are proposed. Results on both synthetic and real sequences are reported to confirm validity of our solution.