Exploiting Redundancy of Purposive Modules in the Context of Active Vision

It is becoming increasingly clear that the robustness demonstrated by biological vision systems is in large part due to their ability to actively integrate (fuse) 1 information from a number of similar or diiering visual cues 34, 2]. In addition to active integration, the perception{action nature of biological systems relies upon the ability to eeectively compose behaviors in an event driven manner. Providing mechanical vision systems with capabilities similar to those possessed by biological systems therefore entails developing appropriate tools and techniques for eeective integration and behavior composition. In this paper, we address two issues. First, we present a uniied approach for handling both integration and process composition which combines a theoretical framework which provides a uniform description of teams of behaviors that are committed to achieving a speciic goal through common eeort and a well known process composition model. Our approach is implemented in a working system called the AV-shell which provides the ability to specify and implement tasks which make use of integration and process composition according to our approach. Secondly, we address the issue of integration in the active vision activity of smooth pursuit. We have experimented with the fusion of four techniques for implementing smooth pursuit such as template matching and image diierencing. We discuss each technique focusing on strengths and weaknesses, then show that fusing the techniques according to our formal framework improves tracking. 1 In this work, the terms active integration and fusion are used interchangably