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 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 contextual 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.