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

Estimating depth from line drawing

Varley, Peter A. C. and Martin, Ralph Robert 2002. Estimating depth from line drawing. Presented at: Seventh ACM Symposium on Solid Modeling and Applications, Saarbrućken, Germany, 17-21 June 2002. Proceedings of the seventh ACM symposium on Solid modeling and applications. New York, NY: ACM, pp. 180-191. 10.1145/566282.566310

Full text not available from this repository.

Abstract

Our goal is unassisted machine interpretation of a single line drawing of an engineering object (with hidden lines removed) as a B-rep model. As part of this process, we seek to deduce a frontal geometry of the object, a 3D geometric realisation of that part of the object visible in the drawing. Inflation takes a drawing in which all lines have been line-labelled, and creates the frontal geometry by adding a z-coordinate to the x- and y-coordinates of each junction. This depth information comes from compliance functions, interpretations of drawing features expressed as equations in junction z-coordinates. We examine several compliance functions, and assessing their use in interpretation of engineering objects. We also describe a compliance function based on junction labels, and remove its previous restriction to trihedral vertices. We give a comparative analysis of applying combinations of compliance functions to a set of test drawings. As a result, we recommend using edge parallelism in combination with either corner orthogonality or junction label pairs, the latter being more reliable in general. Additional use of face planarity compliance is often beneficial and even necessary.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: sketch input, B-rep models
Additional Information: SMA '02
Publisher: ACM
ISBN: 1581135068
Related URLs:
Last Modified: 04 Jun 2017 02:58
URI: http://orca-mwe.cf.ac.uk/id/eprint/14815

Citation Data

Cited 41 times in Google Scholar. View in Google Scholar

Actions (repository staff only)

Edit Item Edit Item