This paper has two coupled objectives: estimating motion and tracking a given object on an image sequence. It relies on a data assimilation approach, that solves evolution equations of motion, those of image brightness, and those of the distance map modeling the object's boundary. The two last express the optical flow constraint, which assumes that image brightness and distance map are advected by velocity. The method assimilates contour points by an innovative approach combining two criteria. First, the boundary of the object should match contour points at acquisition dates; second, the control of the distance between each pixel and the object's boundary allows to better motion estimation on the whole domain. The method is tested on synthetic data and satellite acquisitions.