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Can machines interpret line drawings?

Varley, P. A. C., Martin, Ralph Robert and Suzuki, H. 2004. Can machines interpret line drawings? Presented at: Eurographics Workshop on Sketch-Based Interfaces and Modeling 2004, Grenoble, France, 30 – 31 August 2004. Published in: Hughes, J. F. and Jorge, J. A. eds. Sketch-based interfaces and modeling 2004: Eurographics symposium proceedings. Aire-la-Ville, Switzerland: Eurographics Association, pp. 107-116.

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Abstract

Engineering design would be easier if a computer could interpret initial concept drawings. We outline an approach for automated interpretation of line drawings of polyhedra, and summarise what is already possible, what developments can be expected in the near future, and which areas remain problematic. We illustrate this with particular reference to our own system, RIBALD, summarising the published state of the art, and discussing recent unpublished improvements to RIBALD. In general, successful interpretation depends on two factors: the number of lines, and whether or not the drawing can be classified as a member of special shape class (e.g. an extrusion or normalon). The state-of-the-art achieves correct interpretation of extrusions of any size and most normalons of 20—30 lines, but drawings of only 10—20 lines can be problematic for unclassified objects.Despite successes, there are caseswhere the desired interpretation is obvious to a human but cannot be determined by currently-available algorithms. We give examples both of our successes and of typical cases where human skill cannot be replicated.

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
Q Science > QA Mathematics > QA76 Computer software
Additional Information: https://www.eg.org/index.php/about-eg/working-groups/67-about-eg/working-groups/264-sbim-report-2004
Publisher: Eurographics Association
ISBN: 3905673169
Last Modified: 04 Jun 2017 04:44
URI: http://orca-mwe.cf.ac.uk/id/eprint/43906

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