Computer Vision, IEEE International Conference on (1995)
Massachusetts Institute of Technology, Cambridge, Massachusetts
June 20, 1995 to June 23, 1995
R.C. Wilson , Dept. of Comput. Sci., York Univ., UK
E.R. Hancock , Dept. of Comput. Sci., York Univ., UK
The paper describes a novel approach to relational matching problems in machine vision. Rather than matching static scene descriptions, the approach adopts an active representation of the data to be matched. This representation is iteratively reconfigured to increase its degree of topological congruency with the model relational structure in a reconstructive matching process. The active reconfiguration of relational structures is controlled by a MAP update process. The final restored graph representation is optimal in the sense that it has maximum a posteriori probability with respect to the available attributes for the objects under match. The benefits of the technique are demonstrated experimentally on the matching of cluttered synthetic aperture radar data to a model in the form of a digital map. The operational limits of the method are established in a simulation study.
active vision; computer vision; image matching; image reconstruction; graph theory; relational matching; dynamic graph structures; machine vision; active representation; iterative reconfiguration; topological congruency; model relational structure; reconstructive matching process; active reconfiguration; relational structures; MAP update process; final restored graph representation; maximum a posteriori probability; cluttered synthetic aperture radar data matching; digital map; operational limits
R. Wilson and E. Hancock, "Relational matching with dynamic graph structures," Computer Vision, IEEE International Conference on(ICCV), Massachusetts Institute of Technology, Cambridge, Massachusetts, 1995, pp. 450.