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Proceedings Paper

A PROLOG Simulator For Studying Visual Learning
Author(s): David M. W. Powers
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Paper Abstract

PROLOG has proven useful as a language for research in Machine Learning, Natural Language and, more recently, as a control language for image processing and visual control of robots. A simulator has been written in PROLOG which allows simulated objects to be manipulated using the same image processing operations as are used in image processing systems. VISISIM allows examination of appropriate heuristics for learning to distinguish significant features with a level of control and a speed beyond real-time real-vision systems. It is designed such that once an acceptable performance has been obtained with the simulator, it may be replaced with another module (e.g. PROVISION) for evaluation in real time on real data. The simulator uses a convexity-based representation which allows explicit control over detail and noise, and parameterization of the image processing operators. VISISIM provides for learnt sequences to be available to the learning system as macros, whilst the learning program itself maintains heuristics about the utility of operators at the level of problem domain and context. VISISIM has been used to simulate a playing card recognition problem and find satisfactory variations of a hand crafted solution used with AUTOVIEW. This, however, was achieved using overly restrictive and unrealistic heuristics. Therefore it is proposed that a Knowledge Engineering approach be taken to the development of more realistic heuristics.

Paper Details

Date Published: 27 March 1989
PDF: 8 pages
Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); doi: 10.1117/12.960309
Show Author Affiliations
David M. W. Powers, Macquarie University (Australia)

Published in SPIE Proceedings Vol. 1002:
Intelligent Robots and Computer Vision VII
David P. Casasent, Editor(s)

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