Face Detection Using Beta Wavelet Filter and Cascade Classifier Entrained with Adaboost

被引：1

作者：

Afdhal, Rim ^{[1
]}

Bahar, Akram ^{[1
]}

Ejbali, Ridha ^{[1
]}

Zaied, Mourad ^{[1
]}

机构：

[1] Univ Sfax, REs Grp Intelligent Machines, Soukra St,BP 1173, Sfax 3038, Tunisia

来源：

EIGHTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2015) | 2015年 / 9875卷

关键词：

Face detection; Viola and Jones' algorithm; Haar descriptors; Beta wavelet; Adaboost;

D O I：

10.1117/12.2229620

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Face detection has been one of the most studied topics in the computer vision literature due to its relevant role in applications such as video surveillance, human computer interface and face image database management. Here, we will present a face detection approach which contains two steps. The first step is training phase based on Adaboost algorithm. The second step is the detection phase. The proposed approach presents an enhancement of Viola and Jones' algorithm by replacing Haar descriptors with Beta wavelet. The obtained results have proved an excellent performance of detection not only when a face is in front of the camera but also when it is oriented towards the right or the left. Moreover, thanks to the start period needed for the detection, our approach can be applied during a real time experience.

引用

页数：6

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