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SuperMatching: Feature Matching Using Supersymmetric Geometric Constraints
Nov. 2013 (vol. 19 no. 11)
pp. 1885-1894
Zhi-Quan Cheng, Nat. Lab. for Parallel & Distrib. Process., Nat. Univ. of Defense Technol., Changsha, China
Yin Chen, Nat. Lab. for Parallel & Distrib. Process., Nat. Univ. of Defense Technol., Changsha, China
R. R. Martin, Sch. of Comput. Sci. & Inf., Cardiff Univ., Cardiff, UK
Yu-Kun Lai, Sch. of Comput. Sci. & Inf., Cardiff Univ., Cardiff, UK
Aiping Wang, Nat. Lab. for Parallel & Distrib. Process., Nat. Univ. of Defense Technol., Changsha, China
Feature matching is a challenging problem at the heart of numerous computer graphics and computer vision applications. We present the SuperMatching algorithm for finding correspondences between two sets of features. It does so by considering triples or higher order tuples of points, going beyond the pointwise and pairwise approaches typically used. SuperMatching is formulated using a supersymmetric tensor representing an affinity metric that takes into account feature similarity and geometric constraints between features: Feature matching is cast as a higher order graph matching problem. SuperMatching takes advantage of supersymmetry to devise an efficient sampling strategy to estimate the affinity tensor, as well as to store the estimated tensor compactly. Matching is performed by an efficient higher order power iteration approach that takes advantage of this compact representation. Experiments on both synthetic and real data show that SuperMatching provides more accurate feature matching than other state-of-the-art approaches for a wide range of 2D and 3D features, with competitive computational cost.
Index Terms:
Tensile stress,Vectors,Shape,Transmission line matrix methods,Educational institutions,Accuracy,Computational efficiency,supersymmetric tensor,Feature matching,geometric constraints
Citation:
Zhi-Quan Cheng, Yin Chen, R. R. Martin, Yu-Kun Lai, Aiping Wang, "SuperMatching: Feature Matching Using Supersymmetric Geometric Constraints," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 11, pp. 1885-1894, Nov. 2013, doi:10.1109/TVCG.2013.15
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