Visual tracking system for a mobile robot using colour histograms

Abstract This work describes the visual system of a mobile robot based on a pan-tilt, structure which has been endowed with the ability of tracking moving object using merely colour information. Moving objects in the field of view of the camera are detected and the colour feature of the most relevant regions is selected as the pattern to follow. Colour histograms are used as reliable descriptors to model the appearance of objects. In order to handle with illumination changes a simple adaptation scheme is used. Results show that this system is reliable and fast enough to perform real time tracking of a moving object.

[1]  Ren C. Luo,et al.  Visual tracking using adaptive color histogram model , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[2]  Lionel Prevost,et al.  Automatic allograph selection and multiple expert classification for totally unconstrained handwritten character recognition , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[3]  A. Sanfeliu,et al.  New approaches for colour histogram adaptation in face tracking tasks , 2002, Object recognition supported by user interaction for service robots.

[4]  Seong-Dae Kim,et al.  Moving target tracking algorithm based on the confidence measure of motion vectors , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[5]  Shyang Chang,et al.  A video tracking system with adaptive predictors , 1992, Pattern Recognit..

[6]  Tsukasa Ogasawara,et al.  Online visual learning method for color image segmentation and object tracking , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[7]  Shaogang Gong,et al.  Tracking colour objects using adaptive mixture models , 1999, Image Vis. Comput..

[8]  Ulrich Kressel,et al.  Tracking non-rigid, moving objects based on color cluster flow , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Dimitris P. Tsakiris,et al.  On the visual mathematics of tracking , 1991, Image Vis. Comput..

[10]  Gonzalo R. Arce,et al.  Multichannel image compression by bijection mappings onto zero-trees , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[11]  Brian V. Funt,et al.  Color Constant Color Indexing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  R. Schuster.  Color object tracking with adaptive modeling , 1994 .

[13]  José Santos-Victor,et al.  Robust visual tracking by an active observer , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[14]  Hyung-Il Choi,et al.  Moving object tracking using active models , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[15]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[16]  Tomas Uhlin,et al.  Closing the loop: detection and pursuit of a moving object by a moving observer , 1996, Image Vis. Comput..

[17]  Bernt Schiele,et al.  Object Recognition Using Multidimensional Receptive Field Histograms , 1996, ECCV.