Tracking Objects using Recognition

Randal C. Nelson and Isaac Green
Department of Computer Science
University of Rochester
Rochester, NY 14627

Abstract: Tracking is frequently considered a frame-to-frame operation. As such, object recognition techniques are generally too slow to be used for tracking. There are domains, however, where the objects of interest do not move most of the time. In these domains, it is possible to watch for activity in the scene and then apply object recognition techniques to find the object's new location. This makes tracking a discrete process of watching for object disappearances and reappearances. We have developed a memory assistance tool that uses this approach to help people with slight to moderate memory loss keep track of important objects around the house. The system is currently deployed in a prototype smart home.