ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Curves Matching Using Geodesic Paths
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Continuous curve matching with scale-space curvature and extrema-based scale selection
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
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This paper introduces a new general purpose algorithm that allows the optimal geometric match between contours to be determined, that is the transformation yielding a minimal deformation is obtained. The algorithm relies only on the geometric properties of the contours and does not call for any other constraint, so that it is particularly suitable when no parameterization of title deformation is available or desirable. Contour deformation is explicitly incorporated in the computation, allowing for a thorough use of all geometric information available. Moreover, no discretization is involved in the computation, resulting in two main advantages: first, the algorithm is robust to differences in the segmentation of contours and allows the matching of polygonal approximations of contours with very little loss of precision, second, subpixel precision matching can be achieved.