Title :
Learning system for mobile robot detection and tracking
Author :
Bousnina, Sonda ; Ammar, Boudour ; Baklouti, Nesrine ; Alimi, Adel M.
Author_Institution :
REGIM: Res. Groups on Intell. Machines, Univ. of Sfax, Sfax, Tunisia
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.
Keywords :
Gabor filters; Kalman filters; feature extraction; image classification; image sequences; learning (artificial intelligence); mobile robots; object detection; object tracking; robot vision; support vector machines; target tracking; video signal processing; Gabor filter; Kalman filter; SVM classifier; computer vision; learning system; mobile robot detection; mobile robot tracking; robot feature extraction; support vector machine classifier; target-tracking system; video sequences; visual detection; visual tracking; Feature extraction; Gabor filters; Kalman filters; Service robots; Support vector machines; Tracking; SVM; feature extraction; gabor filter; kalman filter; object detction; object tracking; robotics;
Conference_Titel :
Communications and Information Technology (ICCIT), 2012 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-1949-2
DOI :
10.1109/ICCITechnol.2012.6285831
