Knowledge-based control of vision systems

被引:18
|
作者
Shekhar, C [1 ]
Moisan, S
Vincent, R
Burlina, P
Chellappa, R
机构
[1] Univ Maryland, Ctr Automat Res, College Pk, MD 20742 USA
[2] INRIA Sophia Antipolis, Sophia Antipolis, France
[3] Univ Massachusetts, Dept Comp Sci, Amherst, MA 01003 USA
关键词
vision system; knowledge-based control; self-tuning; algorithm selection; parameter tuning;
D O I
10.1016/S0262-8856(98)00137-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a framework for the development of vision systems that incorporate, along with the executable computer algorithms, the problem-solving knowledge required to obtain optimal performance from them. In this approach, the user provides the input data, specifies the vision task to be performed, and then provides feedback in the form of qualitative evaluations of the results obtained. These assessments are interpreted in a knowledge-based framework to automatically select algorithms and set parameters until results of the desired quality are obtained. This approach is illustrated on two real applications, and examples from the knowledge bases developed are discussed in detail. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
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页码:667 / 683
页数:17
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