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DAGSTUHL
2006

Many-to-Many Feature Matching in Object Recognition

8 years 11 months ago
Many-to-Many Feature Matching in Object Recognition
One of the bottlenecks of current recognition (and graph matching) systems is their assumption of one-to-one feature (node) correspondence. This assumption breaks down in the generic object recognition task where, for example, a collection of features at one scale (in one image) may correspond to a single feature at a coarser scale (in the second image). Generic object recognition therefore requires the ability to match features many-to-many. In this paper, we will review our progress on three independent object recognition problems, each formulated as a graph matching problem and each solving the many-to-many matching problem in a different way. First, we explore the problem of learning a 2-D shape class prototype (represented as a graph) from a set of object exemplars (also represented as graphs) belonging to the class, in which there may be no one-to-one correspondence among extracted features. Next, we define a low-dimensional, spectral encoding of graph structure and use it to mat...
Ali Shokoufandeh, Yakov Keselman, M. Fatih Demirci
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where DAGSTUHL
Authors Ali Shokoufandeh, Yakov Keselman, M. Fatih Demirci, Diego Macrini, Sven J. Dickinson
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