Publication
A new graph matching method for point-set correspondence using the EM algorithm and Softassign
Journal Article (2012)
Journal
Computer Vision and Image Understanding
Pages
292-304
Volume
116
Number
2
Doc link
http://dx.doi.org/10.1016/j.cviu.2011.10.009
File
Abstract
Finding correspondences between two point-sets is a common step in many vision applications (e.g., image matching or shape retrieval). We present a graph matching method to solve the point-set correspondence problem, which is posed as one of mixture modelling. Our mixture model encompasses a model of structural coherence and a model of affine-invariant geometrical errors. Instead of absolute positions, the geometrical positions are represented as relative positions of the points with respect to each other. We derive the Expectation–Maximization algorithm for our mixture model. In this way, the graph matching problem is approximated, in a principled way, as a succession of assignment problems which are solved using Softassign. Unlike other approaches, we use a true continuous underlying correspondence variable. We develop effective mechanisms to detect outliers. This is a useful technique for improving results in the presence of clutter. We evaluate the ability of our method to locate proper matches as well as to recognize object categories in a series of registration and recognition experiments. Our method compares favourably to other graph matching methods as well as to point-set registration methods and outlier rejectors.
Categories
computer vision, image matching, pattern matching, pattern recognition.
Author keywords
correspondence problem, graph matching, affine registration, outlier detection, expectation maximization, Softassign
Scientific reference
G. Sanroma, R. Alquézar Mancho and F. Serratosa i Casanelles. A new graph matching method for point-set correspondence using the EM algorithm and Softassign. Computer Vision and Image Understanding, 116(2): 292-304, 2012.
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