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* Corresponding author 1 The Robotics Institute 2 EPIDAURE - Medical imaging and robotics CRISAM - Inria Sophia Antipolis - Méditerranée

Abstract : We introduce a new surface representation for recognizing curved objects. Our approach begins by representing an object by a discrete mesh of points built from range data or from a geometric model of the object. The mesh is computed from the data by deforming a standard shaped mesh, for example, an ellipsoid, until it fits the surface of the object. We define local regularity constraints that the mesh must satisfy. We then define a canonical mapping between the mesh describing the object and a standard spherical mesh. A surface curvature index that is poseinvariant is stored at every node of the mesh. We use this object representation for recognition by comparing the spherical model of a reference object with the model extracted from a new observed scene. We show how the similarity between reference model and observed data can be evaluated and we show how the pose of the reference object in the observed scene can be easily computed using this representation. We present results on real range images which show that this approach to modelling and recognizing 3D objects has three main advantages:

Keywords : Computer vision Data mining Deformable models Distributed computing Face recognition Image recognition Layout Shape Solid modeling Surface fitting

Author: Martial Hébert - Katsuchi Ikeuchi - Hervé Delingette -

Source: https://hal.archives-ouvertes.fr/


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