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Proceedings Paper

An Interactive Concept Classifier For Scene Analysis
Author(s): Brian Garner; Betty Cheng; Daniel Lui
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Paper Abstract

Scene analysis and scene understanding are acknowledged to require not only the matching of individual object shapes and texture, but also to involve reasoning about the spatial and contextual relationships among objects, so as to provide the basis for a general, real-time knowledge-based interpretation system1. In this paper, semantic information and pragmatics are used to identify and classify both individual objects and sub-scenes (concepts) in the scene analysis process. The use of an interactive concept classifier for scene analysis permits the study of adaptive concept classification and model-directed reasoning for image understanding. A reasoning engine that automatically generates (proposes) recognition strategies is now in prospect based on this approach.

Paper Details

Date Published: 1 March 1990
PDF: 8 pages
Proc. SPIE 1193, Intelligent Robots and Computer Vision VIII: Systems and Applications, (1 March 1990); doi: 10.1117/12.969812
Show Author Affiliations
Brian Garner, DEAKIN University (Australia)
Betty Cheng, DEAKIN University (Australia)
Daniel Lui, DEAKIN University (Australia)

Published in SPIE Proceedings Vol. 1193:
Intelligent Robots and Computer Vision VIII: Systems and Applications
Bruce G. Batchelor, Editor(s)

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