Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Recognizing geometric patterns for beautification of reconstructed solid models

Langbein, Frank Curd, Mills, B. I., Marshall, Andrew David and Martin, Ralph Robert 2001. Recognizing geometric patterns for beautification of reconstructed solid models. Presented at: SMI 2001 International Conference on Shape Modeling and Applications, Genova, Italy, 7-11 May 2001. Proceedings of the SMI 2001 International Conference on Shape Modeling and Applications. IEEE, pp. 10-19. 10.1109/SMA.2001.923370

[img]
Preview
PDF - Accepted Post-Print Version
Download (331kB) | Preview

Abstract

Boundary representation models reconstructed from 3D range data suffer from various inaccuracies caused by noise in the data and the model building software. The quality of such models can be improved in a beautification step, which finds regular geometric patterns approximately present in the model and imposes a maximal consistent subset of constraints deduced from these patterns on the model. This paper presents analysis methods seeking geometric patterns defined by similarities. Their specific types are derived from a part survey estimating the frequencies of the patterns in simple mechanical components. The methods seek clusters of similar objects which describe properties of faces, loops, edges and vertices, try to find special values representing the clusters, and seek approximate symmetries of the model. Experiments show that the patterns detected appear to be suitable for the subsequent beautification steps

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Additional Information: “© © 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
Publisher: IEEE
ISBN: 0769508537
Related URLs:
Date of First Compliant Deposit: 30 March 2016
Last Modified: 09 May 2019 20:02
URI: http://orca-mwe.cf.ac.uk/id/eprint/31752

Citation Data

Cited 21 times in Google Scholar. View in Google Scholar

Cited 16 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics