Matrix analysis
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional binary search trees used for associative searching
Communications of the ACM
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Global Solution to Sparse Correspondence Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Multiple Salient Closed Contours from Real Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Vision-based global localization for mobile robots with hybrid maps of objects and spatial layouts
Information Sciences: an International Journal
Link analysis, eigenvectors and stability
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Reweighted random walks for graph matching
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Hyper-graph matching via reweighted random walks
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
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Establishing consistent correspondences between two sets of features is a fundamental problem in computer vision. This problem can be well formulated as graph matching in which nodes and edges represent feature points and pairwise relationships between feature points, respectively. Spectral matching [19] is the state-of-the-art eigenvector-based method for graph matching. The spectral matching algorithm has been used successfully for small data, but its heavy memory requirement limited the maximum data sizes and contexts it can be used. In this paper, we propose FaSM, a fast and scalable approximate spectral matching algorithm. The main ideas are twofold. First, we exploit the redundancy in the data generation process to approximate the affinity matrix with the linear combination of Kronecker products between bases and index matrices. The bases and index matrices are highly compressed representation of the approximated affinity matrix, requiring much smaller memory than in previous works which store the whole affinity matrix. Second, we compute the eigenvector of the approximated affinity matrix using the small bases and index matrices without explicitly materializing the approximated matrix. Experimental results show that our proposed method is up to 33x faster, requiring up to 645x smaller memory than the exact algorithm, with little or no loss of accuracy.