In this paper we present the design and implementation of a novel low-cost active vision system for robotic applications. The system is comprised of two parts: A 4-DOF trinocular active camera head and a DSP-based image acquisition and processing board. Design issues and tradeoffs are discussed. The performance of the system is evaluated by running an edge-based object tracking algorithm that is also presented in this paper. Experimental results show that the system is capable of tracking objects at 30 frames/sec.

In this paper a system that successfully detects stationary objects in indoor scenes is presented. The doors and ceiling lamps have been chosen to be detected in the initial phase of the authors' system. The scene was divided into four different regions, The edges resulting from the walls/ceiling and the walls/floor intersections are the boundaries that separate the different regions. The use of the log-polar mapping transforms the problem of finding four edges of unknown orientations, that separated the different regions, into finding four horizontal edges. The log-polar map was performed such that it possesses the varying resolution property. The objects were detected using model-matching in the log-polar domain. The varying resolution property of the mapping simplified the model-matching problem. The detection (of edges and then objects) was very fast due to the small size of the log-polar image (64/spl times/64) pixels.>