2004
DOI: 10.1016/s0010-4485(03)00094-0
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A cellular topology-based approach to generating progressive solid models from feature-centric models

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Cited by 48 publications
(39 citation statements)
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“…In case of volumetric entity based techniques, the features are simplified by operating on volumetric entities from the model. The major techniques reported under this category are effective volume [Lee05a,Choi02], cellular representation [Lee04,Lim04], and voxel [He95,Andu02] based approaches. In the explicit feature representation based techniques, the feature information and semantics is explicitly extracted from CAD model or is present in the model in addition to geometric and topological data.…”
Section: Terminologymentioning
confidence: 99%
See 3 more Smart Citations
“…In case of volumetric entity based techniques, the features are simplified by operating on volumetric entities from the model. The major techniques reported under this category are effective volume [Lee05a,Choi02], cellular representation [Lee04,Lim04], and voxel [He95,Andu02] based approaches. In the explicit feature representation based techniques, the feature information and semantics is explicitly extracted from CAD model or is present in the model in addition to geometric and topological data.…”
Section: Terminologymentioning
confidence: 99%
“…The entities are selected for removal based on predefined error metrics that evaluate the geometric impact of their removal. One of the reported error metrics used is quadric error [Garl97,Lee04]. Using the fact, that each vertex is an intersection of several planes, the quadric matrix Q (a 4 x 4 symmetric matrix) is defined for very vertex by aggregating the coefficients of equation of the planes in a way such that the quadric error (e) associated with the given vertex…”
Section: Terminologymentioning
confidence: 99%
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“…However, at present, the cellular topology has only been applied to 3D features. The cellular topology is also used for collaborative design (Wu and Sarma 2001;Lee et al 2004) and efficient feature recognition (Woo 2003).…”
Section: Multiple-view Geometric Representationmentioning
confidence: 99%