Mass-Preserving Maps for Registration and Visual Tracking

Abstract

©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/.2001.980968Presented at the 40th IEEE Conference on Decision and Control, Orlando, Florida USA, December 2001.We consider a new method for an important aspect of the visual tracking problem. Tracking in the presence of a disturbance is a classical control issue, but because of the highly uncertain nature of the disturbance, this type of problem is very difficult. A key issue in many visual tracking tasks is that of registration. Image registration is the process of establishing a common geometric reference frame among several data sets taken at different times. In this paper, we propose a method of registration based on the Monge-Kantorovich problem of optimal mass transport. We argue that such an approach can also be very useful for several problems in controlled active vision