Abstract
Since the two-view orthographic representation of a 3D object is ambiguous, it requires a numerous amount of combinatorial searches in the process of reconstruction. This paper presents an efficient algorithm for reconstructing polyhedral 3D objects from two-view drawings. The main feature of the algorithm is to improve the reconstruction process speed. First, the partially constructed objects are reconstructed from the restricted candidate faces corresponding to each area on the two-view drawings. Then the complete objects are obtained from the partially constructed objects by adding perpendicular faces with geometrical validity. By limiting the number of candidate faces corresponding to areas only, the combinatorial search space can be considerably reduced. In addition, the reconstruction finds the most plausible 3D object that human observers are most likely to select first among the given multiple solutions. Several examples from a working implementation are given to demonstrate the completeness of the algorithm.
Original language | English |
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Title of host publication | Computer Vision - ACCV 1998 - 3rd Asian Conference on Computer Vision, Proceedings |
Editors | Roland Chin, Ting-Chuen Pong |
Publisher | Springer Verlag |
Pages | 241-248 |
Number of pages | 8 |
ISBN (Print) | 3540639314, 9783540639312 |
DOIs | |
Publication status | Published - 1997 |
Event | 3rd Asian Conference on Computer Vision, ACCV 1998 - Hong Kong, Hong Kong Duration: 1998 Jan 8 → 1998 Jan 10 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 1352 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 3rd Asian Conference on Computer Vision, ACCV 1998 |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 98/1/8 → 98/1/10 |
Bibliographical note
Publisher Copyright:© 1997, Springer Verlag. All rights reserved.
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science