THE REDUCTION OF THE FALSE POSITIVE DETECTIONS NUMBER FOR THE ADABOOST CLASSIFIER

被引：0
|
作者：
Popa, Mircea
Majdik, Andras
Lazea, Gheorghe
机构：
来源：
ANNALS OF DAAAM FOR 2009 & PROCEEDINGS OF THE 20TH INTERNATIONAL DAAAM SYMPOSIUM | 2009年 / 20卷
关键词：
adaboost variant; object recognition; people detection;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a variant of the Adaboost algorithm. A new weighting mechanism, which considers image feature domains instead of their values, is proposed in order to reduce the number of false positive detections while maintaining the precision of the Adaboost classifier. The method is exemplified on a vision based people detection application.
引用
收藏
页码：1093 / 1094
页数：2
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