Characterization of Similar Areas of Two 2D Point Clouds

Abstract : We here present a new approach to characterize similar areas of two 2D point clouds, which is a major issue in Pattern Recognition and Image Analysis. To do so, we define a similarity measure that takes into account several criteria such as invariance by rotation, outlier elimination, and one-dimensional structure enhancement. We use this similarity measure to associate locations from one cloud to the other, to use this result in the frame of a registration process between these two point clouds. Our main contributions are the integration of various one-dimensional structure representations into a unified formalism, and the design of a robust estimator to evaluate the common information related to these structures. Finally, we show how to use this approach to register images of different modalities.
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Contributeur : Sébastien Mavromatis <>
Soumis le : dimanche 13 mars 2016 - 22:47:04
Dernière modification le : mercredi 12 septembre 2018 - 01:27:03



Sébastien Mavromatis, Christophe Palmann, Jean Sequeira. Characterization of Similar Areas of Two 2D Point Clouds. Advances in Visual Computing, Jul 2012, Crete, Greece. Springer Berlin Heidelberg, pp.509--516, 2012, 〈10.1007/978-3-642-33191-6_50〉. 〈hal-01287589〉



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