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

页码：1093 / 1094

页数：2

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