Segmentation and estimation of image motion by a robust method

Locating the image of moving objects in a scene and estimating their motion are among the main issues in dynamic scene analysis. They are relevant to a large variety of tasks such as autonomous navigation, tracking, obstacle detection and surveillance. A central problem faced by existing methods is related to the occurrence of motion boundaries. With the aim of achieving correct and robust interpretation in the face of occurrence of motion boundaries, noise, and insufficiently informative image brightness pattern regions, the method we propose is articulated about the fundamental concepts of gradient-based multiconstraint, statistically robust regression, and regularization