Optimization in Model Matching and Perceptual Organization

被引：34

作者：

Mjolsness, Eric ^{[1
]}

Gindi, Gene ^{[2
]}

Anandan, P. ^{[1
]}

机构：

[1] Yale Univ, Dept Comp Sci, POB 2158, New Haven, CT 06520 USA

[2] Yale Univ, Dept Elect Engn, New Haven, CT 06520 USA

来源：

NEURAL COMPUTATION | 1989年 / 1卷 / 02期

关键词：

D O I：

10.1162/neco.1989.1.2.218

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce an optimization approach for solving problems in computer vision that involve multiple levels of abstraction. Our objective functions include compositional and specialization hierarchies. We cast vision problems as inexact graph matching problems, formulate graph matching in terms of constrained optimization, and use analog neural networks to perform the optimization. The method is applicable to perceptual grouping and model matching. Preliminary experimental results are shown.

引用

页码：218 / 229

页数：12

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