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Publication in EndNote Format

%0 Report %@ 406 %A Pentland, Alex P. %T Recognition By Parts %C 333 Ravenswood Ave., Menlo Park, CA 94025 %I AI Center, SRI International %D 1987 %K Vision!Part recognition %X To have a general-purpose machine vision capability, we must be able to recognize things; we argue that most natural objects have a part structure that we can recover from image data and thus use as the basis for ``general-purpose’’ recognition. We describe a ``parts’’ representation that is fairly general purpose, despite having only a small number of parameters. Having this expressive power captured by a small number of parameters allows us to approach the problem of recovering an object’s part structure by use of the model-based vision technique of global search-and-match. We present several examples of recovering part structure using various types of range imagery to show that the recovery procedure is robust. %O Originally published December 16, 1986. This is revised version, dated August 25, 1987. %U http://www.ai.sri.com/pubs/files/559.pdf

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