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Robust geometric matching for 3D object recognition

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1 Author(s)
Cass, T.A. ; Xerox Palo Alto Res. Center, CA, USA

This paper considers a model-based approach to identifying and locating known 3D objects in 2D images of a scene containing them via geometric feature matching of model and image data represented in terms of local geometric features. The problems of finding feature correspondences in the presence of geometric uncertainty, missing, and spurious data features are explicitly handled. The fundamentally geometric and combinatorial elements of the feature matching problem are made explicit, and a formulation based on computational geometry is used to achieve a polynomial-time matching approach for which the author can guarantee completeness and correctness. This paper deals primarily with the case of planar objects undergoing full 3D motion and scaled-orthographic projection

Published in:

Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on  (Volume:1 )

Date of Conference:

9-13 Oct 1994