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A General Framework for Curve and Surface Comparison and Registration with Oriented Varifolds
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
This paper introduces a general setting for the construction of data fidelity metrics between oriented or nonoriented geometric shapes like curves, curve sets or surfaces. These metrics are based on the representation of shapes as distributions of their local tangent or normal vectors and the definition of reproducing kernels on these spaces. The construction, that combines in one common setting and extends the previous frameworks of currents and varifolds, provides a very large class of kerneldoi:10.1109/cvpr.2017.487 dblp:conf/cvpr/KaltenmarkCC17 fatcat:5r4puwxkhzdg3kyzqn23jszwsq