Proceedings of the Seventh ACM Symposium on Solid Modeling and Applications - SMA '02 2002
DOI: 10.1145/566294.566295
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Reconstruction of feature volumes and feature suppression

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Cited by 6 publications
(10 citation statements)
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“…Another approach, capable of handling more interacting shape features through an iterative method is presented in Venkataraman and Sohoni (2002), where form feature recognition techniques are used to detect features face-sets, and then a feature is removed before passing to the next iteration, where previously interfering features can be detected.…”
Section: Related Workmentioning
confidence: 99%
“…Another approach, capable of handling more interacting shape features through an iterative method is presented in Venkataraman and Sohoni (2002), where form feature recognition techniques are used to detect features face-sets, and then a feature is removed before passing to the next iteration, where previously interfering features can be detected.…”
Section: Related Workmentioning
confidence: 99%
“…For the "Drum" model in Fig. 6, note that face extension or contraction methods used in previous work, for example in [4], are unable to obtain the simplified top (highlighted in yellow in Fig. 6a) and will fail to repair the model.…”
Section: Implementation and Analysismentioning
confidence: 99%
“…To avoid the complex surface intersection calculation involved frequently in previous works [4], a simple loop decomposition technique is developed where each complex boundary loop of the region to be suppressed is decomposed into several simple co-surface loops. The co-defined edges is a pair of edges with the same underlying curve, which likely depicts the main shape of the original model, and is a good hint of repairing models.…”
Section: Decomposition Of Boundary Loopmentioning
confidence: 99%
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“…Other approaches consist of adapting CAD models directly. For example, feature recognition and extraction processes can be intended to simplify details like fillets and blends [21][22], bosses, pockets [23] and holes. Some of these approaches generate tree-structured simplified models, where each simplification is identified as a feature.…”
Section: Introductionmentioning
confidence: 99%