An algorithm for simultaneous motion estimation and scene segmentation

We present an algorithm that simultaneously performs motion estimation and scene segmentation in image sequences. This algorithm improves upon the traditional approach of using the motion estimates that are obtained separately as input for scene segmentation. Based on the maximum a posteriori probability (MAP) criterion, the interdependence of constraints for motion estimation and scene segmentation are expressed in a Gibbs distribution. The solution is obtained based on the highest confidence first (HCF) and iterated conditional mode (ICM) optimization methods. Experimental results suggest that this algorithm is of potential use for low-bit rate video coding