Matching of affinely invariant regions for visual servoing

This paper develops new image matching techniques for visual servoing based on affine invariants which allow one to deal with large viewpoint changes and that do not rely on specific markers. The only assumption is that there are some locally planar and unoccluded scene regions that have enough structure to be detected in the image. Those regions are classified by a set of illumination and viewpoint invariant features. The features represent the image in a very compact way and allow fast comparison and feature matching between quite different viewpoints. The matching procedure is embedded in a visual servoing system for a mobile robot. Experiments show its potential for navigation with large camera rotations and view point changes in a cluttered environment without the need for artificial landmarks.

[1]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[2]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[3]  H. C. Longuet-Higgins,et al.  A computer algorithm for reconstructing a scene from two projections , 1981, Nature.

[4]  Patrick Rives,et al.  Positioning of a robot with respect to an object, tracking it and estimating its velocity by visual servoing , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[5]  Thomas S. Huang,et al.  Theory of Reconstruction from Image Motion , 1992 .

[6]  Richard I. Hartley,et al.  In defence of the 8-point algorithm , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  S. P. Mudur,et al.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[8]  Gregory Dudek,et al.  Vision-based robot localization without explicit object models , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[9]  Richard I. Hartley,et al.  In Defense of the Eight-Point Algorithm , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Andrew Zisserman,et al.  Wide baseline stereo matching , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  Josef Kittler,et al.  On the correspondence problem for wide angular separation of non-coplanar points , 1998, Image Vis. Comput..

[13]  L. Gool,et al.  Color-Based Moment Invariants for Viewpoint and Illumination Independent Recognition of Planar Color Patterns , 1999 .