Video Segmentation with Superimposed Mobile Maps of Distances


A real-time and reliable automatic video segmentation is one of the outstanding problems in Computer Vision with large applications to compression, transmission and motion analysis. In this paper, we show a novel approach based on the superposition of distance maps linked to centroids of mobile regions acting as attractors of homogenous regions to which different thresholds are applied. The homogeneity of each region is characterized by colour characteristics. The number of colors and the extremal values allowed for parameters corresponding to the shape of regions can be previously configured or learned through an unsupervised training. Our realtime processing does not depend on the scene complexity and it is compatible with egomotion, i.e. it is not necessary to discriminate beforehand between foreground and background. Compatibility of our segmentation algorithms with egomotion allows the design of on-line tracking and shots identification for automatic segmentation of video sequences by using a low-level topological representation, which is symbolically represented by means of a kinematic mobile graph.

Cite this paper

@inproceedings{Viloria2004VideoSW, title={Video Segmentation with Superimposed Mobile Maps of Distances}, author={Alejandro Viloria and Javier Finat and M . Gonzalo - Tasis}, year={2004} }