The architecture and performance of the face and eyes detection system based on the Haar cascade classifiers

被引：0
|
作者：
Andrzej Kasinski
Adam Schmidt
机构：
[1] Poznan University of Technology,Institute of Control and Information Engineering
来源：
Pattern Analysis and Applications | 2010年 / 13卷
关键词：
Face detection; Eyes detection; Haar cascade classifiers;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The precise face and eyes detection is essential in many human–machine interface systems. Therefore, it is necessary to develop a reliable and efficient object detection method. In this paper we present the architecture of a hierarchical face and eyes detection system using the Haar cascade classifiers (HCC) augmented with some simple knowledge-based rules. The influence of the training procedure on the performance of the particular HCCs has been investigated. Additionally, we compared the efficiency of other authors’ face and eyes HCCs with the efficiency of those trained by us. By applying the proposed system to the set of 10,000 test images we were able to properly detect and precisely localize 94% of the eyes.
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页码：197 / 211
页数：14
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