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Published Articles >> Table of Contents >> Abstract
15th International Conference on Pattern Recognition (ICPR'00) - Volume 1
p. 1720
Recognition and Reconstruction of 3-D Objects Using Model-Based Perceptual Grouping
In Kyu Park, Seoul National University
Sang Uk Lee, Seoul National University
Kyoung Mu Lee, Hong-Ik University
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.905488
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| Abstract |
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In this paper, we address a new algorithm for recognition and reconstruction of 3-D polyhedral objects, based on perceptual grouping and graph search technique. Perceptual grouping is performed in a model-based framework, in which decision tree classifier is employed for learning and retrieving geometric information of the 3-D model object. On the other hand, in order to extract the polygonal patch structure, initial grouping result is represented by a Gestalt graph. Polygonal patch hypotheses are then generated by graph search and verified by the consistency test with the model. In the experiments, it is shown that the model-based grouping reduces the number of the generated hypotheses efficiently, and fi4rthermore, robust recognition and reconstruction are achieved by means of the graph search technique.
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Citation:
In Kyu Park, Sang Uk Lee, Kyoung Mu Lee,
"Recognition and Reconstruction of 3-D Objects Using Model-Based Perceptual Grouping,"
icpr,
p. 1720,
15th International Conference on Pattern Recognition (ICPR'00) - Volume 1,
2000
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