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A Feature-Based Approach to Re-engineering CAD Models from Cross Sections.

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Title: A Feature-Based Approach to Re-engineering CAD Models from Cross Sections.
Authors: Protopsaltis, Antonis I.1 antonis@cs.uoi.gr, Fudos, Ioannis1 fudos@cs.uoi.gr
Source: Computer-Aided Design & Applications. 2010, Vol. 7 Issue 5, p739-757. 19p. 8 Illustrations.
Subjects: Computer-aided design, Mathematical models, Cross-sectional method, Cluster analysis (Statistics), Dimensional analysis, Robust control, Constraint satisfaction
Abstract: We introduce a novel approach to reconstructing 3D objects from cross sections of point clouds acquired by 3D scanning. In this context cross sections are almost planar clusters of 3D points. We first thin each cluster to obtain an ordered one dimensional set of planar points. We then partition the point set to subsets that can be approximated adequately by piecewise quadratic rational Bezier curves using an optimal fitting method. For each curve we select a number of representative points that lie on the fitting curves which are then used for reconstructing the object surface. Inter-cross section and intra-cross section constraints are imposed to support parameterization and editing of the derived model. Shape and topological differences between adjacent object contours pose several issues for the 3D reconstruction process. By using the contour skeleton information we produce intermediate cross sections representing places where ramifications occur to achieve robust covering (meshing) of adjacent slices. Finally, we present a proof of concept implementation of our method and several examples that demonstrate its effectiveness and efficiency. [ABSTRACT FROM AUTHOR]
Copyright of Computer-Aided Design & Applications is the property of Computer-Aided Design & Applications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22Computer-Aided+Design+%26+Applications%22">Computer-Aided Design & Applications</searchLink>. 2010, Vol. 7 Issue 5, p739-757. 19p. 8 Illustrations.
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  Data: <searchLink fieldCode="DE" term="%22Computer-aided+design%22">Computer-aided design</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Dimensional+analysis%22">Dimensional analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br /><searchLink fieldCode="DE" term="%22Constraint+satisfaction%22">Constraint satisfaction</searchLink>
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  Data: We introduce a novel approach to reconstructing 3D objects from cross sections of point clouds acquired by 3D scanning. In this context cross sections are almost planar clusters of 3D points. We first thin each cluster to obtain an ordered one dimensional set of planar points. We then partition the point set to subsets that can be approximated adequately by piecewise quadratic rational Bezier curves using an optimal fitting method. For each curve we select a number of representative points that lie on the fitting curves which are then used for reconstructing the object surface. Inter-cross section and intra-cross section constraints are imposed to support parameterization and editing of the derived model. Shape and topological differences between adjacent object contours pose several issues for the 3D reconstruction process. By using the contour skeleton information we produce intermediate cross sections representing places where ramifications occur to achieve robust covering (meshing) of adjacent slices. Finally, we present a proof of concept implementation of our method and several examples that demonstrate its effectiveness and efficiency. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer-Aided Design & Applications is the property of Computer-Aided Design & Applications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Cross-sectional method
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      – SubjectFull: Cluster analysis (Statistics)
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      – SubjectFull: Robust control
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