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

fYear

2012

fDate

26-28 June 2012

Firstpage

384

Lastpage

389

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Information Technology (ICCIT), 2012 International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-1949-2

Type

conf

DOI

10.1109/ICCITechnol.2012.6285831

Filename

6285831