A framework for statistical 3-D object recognition

doi:10.1016/S0167-8655(97)00139-6

A framework for statistical 3-D object recognition

1997-11-01

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DOI：10.1016/S0167-8655(97)00139-6

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In this contribution we describe an object-oriented software architecture for image segmentation, 3-D pose estimation as well as Bayesian object recognition: models are represented by densities, model generation corresponds to parameter estimation tasks, and the identification applies the Bayesian decision rule. We show results of 3-D object recognition experiments based on the observation of 2-D points or lines. (C) 1997 Elsevier Science B.V.

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object-oriented programming

statistical object recognition

A framework for statistical 3-D object recognition

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