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Description: J-linkage 算法，可以用于多体拟合的一种策略，优于Multi-ransac-This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual data representation. Each point is represented with the characteristic function of the set of random models that fit the point. A tailored agglomerative clustering, called L-linkage, is used to group points belonging to the same model. The method does not require prior speci?cation of the number of models, nor it necessitate parameters tuning. Experimental results demonstrate thesuperior performances of the algorithm.
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Author: tomas |
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