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Proceedings Paper

Evidence-Based 3D Object Recognition
Author(s): Anil K. Jain; Richard Hoffman
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Paper Abstract

An evidence-based recognition technique is defined which identifies 3D objects by looking for notable features of objects. 3D surface patch information is used to derive a representation of objects from their range images. A list of salient or evidence features with corresponding degrees of evidence of the various objects in the database forms the core of an object recognition system. Occurrences of these salient features are interpreted as evidence for or against the hypothesis that a given object occurs in the scene. A measure of similarity between the set of observed features and the set of salient features for a given object in the database is used to determine the identity of an object in the scene or reject the object(s) in the scene as unknown. This procedure has polynomial time complexity and correctly identifies a variety of objects in both synthetic and real range images.

Paper Details

Date Published: 21 August 1987
PDF: 8 pages
Proc. SPIE 0754, Optical and Digital Pattern Recognition, (21 August 1987); doi: 10.1117/12.939992
Show Author Affiliations
Anil K. Jain, Michigan State University (United States)
Richard Hoffman, University of Illinois at Chicago (United States)

Published in SPIE Proceedings Vol. 0754:
Optical and Digital Pattern Recognition
Hua-Kuang Liu; Paul S. Schenker, Editor(s)

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