Graph representation of images in scale-space with application to face detection

被引：0

作者：

Maruta, Hidenori ^{[1
]}

Kozakaya, Tatsuo ^{[2
]}

Koike, Yasuharu ^{[3
]}

Sato, Makoto ^{[3
]}

机构：

[1] Information Science Center, Nagasaki University, Nagasaki-shi, 852-8521, Japan

[2] Toshiba Corporation, Kawasaki-shi, 212-8582, Japan

[3] Precision and Intelligen Laboratory, Tokyo Institute of Technology, Yokohama-shi, 226-8503, Japan

来源：

IEICE Transactions on Information and Systems | 2003年 / E86-D卷 / 07期

关键词：

Face recognition - Feature extraction - Graph theory - Image quality - Image segmentation - Object recognition - Pattern recognition systems;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In the image recognition problem, it is very important how we represent the image. Considering this, we propose a new representational method of images based on the stability in scale-space. In our method, the image is segmented and represented as a hierarchical region graph in scale-space. The object is represented as feature graph, which is subgraph of region graph. In detail, the region graph is defined on the image with the relation of each segment hierarchically. And the feature graph is determined based on the life-time of the graph of the object in scale-space. This life-time means how long feature graph lives when the scale parameter is increased. We apply our method to the face detection problem, which is foundmental and difficult problem in face recognition. We determine the feature graph of the frontal human face statistical point of view. We also build the face detection system using this feature graph to show how our method works efficiently.

引用

页码：1221 / 1227