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ICPR
2010
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Learning an Efficient and Robust Graph Matching Procedure for Specific Object Recognition

8 years 11 months ago
Learning an Efficient and Robust Graph Matching Procedure for Specific Object Recognition
We present a fast and robust graph matching approach for 2D specific object recognition in images. From a small number of training images, a model graph of the object to learn is automatically built. It contains its local keypoints as well as their spatial proximity relationships. Training is based on a selection of the most efficient subgraphs using the mutual information. The detection uses dynamic programming with a lattice and thus is very fast. Experiments demonstrate that the proposed method outperforms the specific object detectors of the state-of-the-art in realistic noise conditions. Keywords-specific object recognition; cascade; graph matching;
Jerome Revaud, Guillaume Lavoue, Yasuo Ariki, Atil
Added 02 Aug 2010
Updated 02 Aug 2010
Type Conference
Year 2010
Where ICPR
Authors Jerome Revaud, Guillaume Lavoue, Yasuo Ariki, Atilla Baskurt
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