Journal
COMPUTER VISION AND IMAGE UNDERSTANDING
Volume 105, Issue 3, Pages 200-217Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.cviu.2006.10.003
Keywords
function based reasoning; recognition; classification; computer vision; raw range images; 3D segmentation
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In this work we propose a probabilistic model for generic object classification from raw range images. Our approach supports a validation process in which classes are verified using a functional class graph in which functional parts and their realization hypotheses are explored. The validation tree is efficiently searched. Some functional requirements are validated in a final procedure for more efficient separation of objects from non-objects. The search employs a knowledge repository mechanism that monotonically adds knowledge during the search and speeds up the classification process. Finally, we describe our implementation and present results of experiments on a database that comprises about 150 real raw range images of object instances from 10 classes. (c) 2006 Elsevier Inc. All rights reserved.
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