CVPR Paper: Probabilistic parameter-free motion detection

T. Veit, F. Cao, P. Bouthemy. Probabilistic parameter-free motion detection. In Conf. Computer Vision and Pattern Recognition, CVPR'04, Washington, DC, June 2004.
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We propose an original probabilistic parameter-free method for the detection of independently moving objects in an image sequence. We apply a probabilistic perceptual principle, the Helmholtz principle, whose main advantage is the automatization of the detection decision, by providing a tight control of the number of false alarms. Not only does this method localize the moving objects but it also answers the preliminary question of the presence of motion. In particular, the method works even when no assumption on motion presence is made. The algorithm is composed of three independent steps: estimation of the dominant image motion, spatial segmentation of object boundaries and independent motion detection itself. We emphasize that none of these steps needs any parameter tuning. Results on real image sequences are reported and validate the proposed approach.

With background paper on grouping.