Limitations of Geometric Hashing in the Presence of Gaussian Noise
This paper presents a detailed error analysis of geometric hashing for 2D object recogition. We analytically derive the probability of false positives and negatives as a function of the number of model and image, features and occlusion, using a 2D Gaussian noise model. The results are presente...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/5956 |