Quadtree-based genetic algorithm and its applications to computer vision

被引：28

作者：

Gong, ML ^{[1
]}

Yang, YH ^{[1
]}

机构：

[1] Univ Alberta, Comp Graph Res Grp, Dept Comp Sci, Edmonton, AB T6G 2E8, Canada

来源：

PATTERN RECOGNITION | 2004年 / 37卷 / 08期

基金：

加拿大自然科学与工程研究理事会;

关键词：

genetic algorithm; ill-posed problems; image segmentation; quad-tree; optimization; stereo vision; motion estimation;

D O I：

10.1016/j.patcog.2004.02.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Many computer vision problems can be formulated as optimization problems. Presented in this paper is a new framework based on the quadtree-based genetic algorithm that can be applied to solve many of these problems. The proposed algorithm incorporates the quadtree structure into the conventional genetic algorithm. The solutions of image-related problems are encoded through encoding the corresponding quadtrees, and therefore, the 2D locality within a solution can be preserved. Examples addressed using the proposed framework include image segmentation, stereo vision, and motion estimation. In all cases, encouraging results are obtained. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：1723 / 1733

页数：11

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