Title :
A region-level graph labeling approach to motion-based segmentation
Author :
Gelgon, Marc ; Bouthemy, Patrick
Author_Institution :
IRISA, Rennes, France
Abstract :
This paper deals with the problem of motion-based segmentation of image sequences. Such partitions are multiple-purpose in dynamic scene analysis. We first extract a spatial texture-based partition using an unsupervised MRF approach. The regions obtained are then grouped according to a motion-based criterion. This grouping process relies on two motion estimation techniques and exploits centextual information between regions. In contrast with clustering techniques, region grouping is formalized as a motion-based graph labeling process, within a Markovian framework. Results on real-world image sequences are shown and validate the proposed method
Keywords :
Markov processes; image segmentation; image sequences; motion estimation; Markovian framework; centextual information; dynamic scene analysis; image sequences; motion-based graph labeling process; motion-based segmentation; region grouping; region-level graph labeling approach; spatial texture-based partition; unsupervised MRF approach; Clustering algorithms; Computer vision; Data mining; Image analysis; Image segmentation; Image sequences; Labeling; Merging; Motion estimation; Partitioning algorithms;
Conference_Titel :
Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Conference_Location :
San Juan
Print_ISBN :
0-8186-7822-4
DOI :
10.1109/CVPR.1997.609374