Estimation of Dense 2-d Motion Based on the Constancy of Intensity Gradient

This paper describes a new approach to the estimation of dense 2-D motion from image sequences. Unlike in many other approaches that assume the constancy of image intensity along motion trajectories, we propose to use a higher order model that permits a variation of such intensity. We deene the structural model that is based on the assumption of intensity gradient constancy along motion trajectories. This model has been proposed before 7], however in formulations that require exact satisfaction of the intensity gradient constraint. Due to inherent noise, aliasing, etc. present in images such solution necessitates additional post-processing, for example smoothing. We propose a diierent approach that is based on simultaneous estimation and smoothing. We formulate the problem using regularization where the assumptions of gradient constancy and of motion smoothness are combined into a single cost function. We minimize this function by an iterative method. We demonstrate estimation results for the original and for the \regularized" approach on natural image sequences.