An Interactive Concept Classifier For Scene Analysis

Brian Garner; Betty Cheng; Daniel Lui

doi:10.1117/12.969812

1 March 1990 An Interactive Concept Classifier For Scene Analysis

Brian Garner, Betty Cheng, Daniel Lui

Proceedings Volume 1193, Intelligent Robots and Computer Vision VIII: Systems and Applications; (1990) https://doi.org/10.1117/12.969812
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

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.

Citation Download Citation

Brian Garner, Betty Cheng, and Daniel Lui "An Interactive Concept Classifier For Scene Analysis", Proc. SPIE 1193, Intelligent Robots and Computer Vision VIII: Systems and Applications, (1 March 1990); https://doi.org/10.1117/12.969812

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