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We describe a procedure which finds a hierarchical clustering by hillclimbing. The cost function we use is a hierarchical extension of the -means cost; our local moves are tree...
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Abstract. The plane-based calibration consists in recovering the internal parameters of the camera from the views of a planar pattern with a known geometric structure. The existing...