DocumentCode :
3209511
Title :
Extraction of line drawing features for object recognition
Author :
Bergevin, Robert ; Levine, Martin D.
Author_Institution :
Res. Center for Intelligent Machines, McGill Univ., Montreal, Que., Canada
Volume :
i
fYear :
1990
fDate :
16-21 Jun 1990
Firstpage :
496
Abstract :
The authors describe the geometrical criteria which define viewpoint-invariant features to be extracted from 2-D line drawings of 3-D objects. They also discuss the extraction of these features, which forms the initial stage of a generic object recognition system, the Primal Access Recognition of Visual Objects (PARVO) system. In this system, part-based qualitative descriptions are built and matched to coarse 3-D object models for recognition. The segmentation and labeling of the constituent parts of an object rely on the 3-D properties inferred from the presence of its 2-D features. The original motivation for PARVO its recognition by components, a theory of human image understanding from the field of psychology. Definitions of the geometrical criteria defining the viewpoint-invariant features are introduced. Examples of results obtained by applying these criteria to a typical line drawing are shown
Keywords :
computer vision; 2-D line drawings; 3-D objects; PARVO; Primal Access Recognition of Visual Objects; computer vision; features extraction; human image understanding; labeling; object recognition; part-based qualitative descriptions; psychology; recognition by components; segmentation; viewpoint-invariant features; Computer vision; Feature extraction; Humans; Image segmentation; Intelligent robots; Labeling; Laboratories; Object recognition; Psychology; Robot vision systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-8186-2062-5
Type :
conf
DOI :
10.1109/ICPR.1990.118153
Filename :
118153
Link To Document :
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