Abstract

A surface feature hypergraph (SFAHG) representation is proposed for the recognition and localization of three-dimensional objects. The hypergraph representation is shown to be viewpoint independent thus resulting in substantial savings in terms of memory for the object model database. The resulting hypergraph matching algorithm integrates both, relational and the rigid pose constraint in a consistent unified manner. The matching algorithm is also shown to have a polynomial order of complexity even in multiple-object scenes with instances of objects partially occluding each other. An algorithm for incrementally constructing the hypergraph representation of an object model from range images of the object taken from different viewpoints is also presented. The hypergraph matching and the hypergraph construction algorithms are shown to be capable of correcting errors in the initial segmentation of the range image. The hypergraph construction algorithm and the matching algorithm are tested on range images of scenes containing multiple three-dimensional objects with partial occlusion.

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