Dynamic aspects in active vision

Abstract

The term active stresses the role of the motion or, generally speaking, the dynamic interaction of the observer with the environment. This concept emphasizes the relevance of determining scene properties from the temporal evolution of image features. Within the active vision approach, two different aspects are considered: the advantages of space-variant vision for dynamic visual processing and the qualitative analysis of optical flow. A space-variant sampling of the image plane has many good properties in relation to active vision. In particular, two examples are presented in which a log-polar representation is used for active vergence control and to estimate the time-to-impact during tracking egomotion. These are just two modules which could fit into a complete active vision system, but already highlight the advantages of space-variant sensing within the active vision paradigm. In the second part of the paper the extraction of qualitative properties from the optical flow is discussed. A new methodology is proposed in which optical flows are analyzed in terms of anomalies as unexpected velocity patterns or inconsistencies with respect to some predicted dynamic feature. Two kinds of knowledge are necessary: about the dynamic of the scene (for example, the approximate motion of the camera) and about the task to be accomplished, which is analogous to (qualitatively) knowing the kind of scene I would expect to see. The first simply implies the measurement of some motion parameters (for example, with inertial sensors) directly on the camera, or to put some constraints in the egomotion. The second requirement implies that the visual process is task-driven. Some examples are presented in which the method is successfully applied to robotic tasks.