DocumentCode :
3084452
Title :
Robust geometric matching for 3D object recognition
Author :
Cass, Todd A.
Author_Institution :
Xerox Palo Alto Res. Center, CA, USA
Volume :
1
fYear :
1994
fDate :
9-13 Oct 1994
Firstpage :
477
Abstract :
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
Keywords :
computational geometry; 2D images; 3D object recognition; combinatorial elements; completeness; computational geometry; correctness; feature correspondences; full 3D motion; geometric feature matching; geometric uncertainty; local geometric features; planar objects; polynomial-time matching approach; robust geometric matching; scaled-orthographic projection; Computational geometry; Contracts; Image recognition; Image segmentation; Layout; Object recognition; Polynomials; Robustness; Solid modeling; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
Type :
conf
DOI :
10.1109/ICPR.1994.576330
Filename :
576330
Link To Document :
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