Contour/Texture Approach for Visual Tracking

In this article, the problem of real-time hybrid contours/texture tracking for planar objects is addressed. On one hand, a lot of methods have been proposed to track objects from their contours. On the other hand, numerous other tracking algorithms deal with texture. In real situations, objects can unfortunately rarely be divided so clearly. Therefore, an hybrid tracking approach, able to mix texture and contour information, appears to be very useful. The proposed approach is very simple and efficient. It is based on image differences, which are the differences between object aspects in the image and aspects predicted using a parametric transformation model. Knowing a difference image, the proposed algorithm only need a matrix multiplication to estimate motion parameters. This is possible due to the use of an off-line learning stage.

[1]  Michel Dhome,et al.  Real time 3D template matching , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[2]  Roberto Cipolla,et al.  Real-time tracking of complex structures with on-line camera calibration , 2002, Image Vis. Comput..

[3]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[4]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[5]  Marco La Cascia,et al.  Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Texture-Mapped 3D Models , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  David J. Fleet,et al.  Robust online appearance models for visual tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Michel Dhome,et al.  Hyperplane Approximation for Template Matching , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Michel Dhome,et al.  A simple and efficient template matching algorithm , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[9]  Hans-Hellmut Nagel,et al.  3D Pose Estimation by Directly Matching Polyhedral Models to Gray Value Gradients , 1997, International Journal of Computer Vision.

[10]  Gregory D. Hager,et al.  Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  David G. Lowe,et al.  Robust model-based motion tracking through the integration of search and estimation , 1992, International Journal of Computer Vision.