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Proceedings Paper

Spatial Reasoning: Learning from Observations
Author(s): Mirsad Hadzikadic; Su-shing Chen
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Paper Abstract

This paper is concerned with a machine learning approach to spatial reasoning, under the goal of developing an intelligent system capable of sensor fusion, scene understanding, reasoning with spatial objects, and improving its performance over time. We integrate an incremental conceptual clustering system (INC) with a com-puter vision system, developed in our Artificial Intelligence and Computer Vision laboratories. The project consists of: (1) developing spatial knowledge models and cognitive functions within a spatial learning system, and (2) evaluating the plausibility, effectiveness, and constraints of the system in both the general-type spatial reasoning tasks in cognitive systems and the following scene analysis/understanding tasks: sensor fusion, object recognition, model instantiation, image/scene description, and reasoning about a scene.

Paper Details

Date Published: 1 March 1990
PDF: 9 pages
Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); doi: 10.1117/12.969980
Show Author Affiliations
Mirsad Hadzikadic, University of North Carolina-Charlotte (United States)
Su-shing Chen, University of North Carolina-Charlotte (United States)

Published in SPIE Proceedings Vol. 1198:
Sensor Fusion II: Human and Machine Strategies
Paul S. Schenker, Editor(s)

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