Learning system for mobile robot detection and tracking

Abstract

Visual detection and tracking is an important and challenging problem in the area of computer vision. Numerous researches have been undergoing. In this paper, we present a target-tracking system specific for mobile robots. We used in our system the Gabor filter to extract the robot features. Robot detection is based on the Support Vector Machine (SVM) classifier. Once the detection is accomplished, the Kalman filter is employed to track the detected robot. Experimental results have been extracted for a set of video sequences with the moving robot at different positions and with a variation of backgrounds.