Learning to track colored objects with log-polar vision
An approach bringing together space-variant vision through a simple color segmentation technique and learning is presented. The proposed approach is employed to control the movement of a 5 degree of freedom (d.o.f.) robotic head. Color information is used to determine the position of the object of interest in the image plane and, consequently, to track it during its motion. The distance of the target from the center of the image is used to feed both a closed-loop and an open-loop controller. Most important, the parameters of the controllers are learnt on-line in a self-supervised fashion. Experiments are presented to demonstrate empirically the feasibility of the approach and its application to a real world control problem. (C) 2004 Elsevier Ltd. All rights reserved.
learning log-polar images gaze control active vision