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一种基于AdaBoost人脸检测算法在Android平台的实现
引用本文:安恒煊,张学习,李超,陈文辉,邹兵.一种基于AdaBoost人脸检测算法在Android平台的实现[J].电子设计工程,2014(8):126-130.
作者姓名:安恒煊  张学习  李超  陈文辉  邹兵
作者单位:[1]广东工业大学自动化学院,广东广州510006 [2]北京航天航空大学,北京100191
摘    要:针对Android系统自带的人脸检测算法不能精确地检测人脸,尤其是带眼镜后,根本无法检测到人脸.本文研究了一种基于Android系统下的AdaBoost人脸检测算法.首先介绍了Android平台下的人脸检测体系结构,然后对AdaBoost人脸检测模块,包括特征值与特征值的计算、AdaBoost分类器、开发环境搭建分别进行了说明.最后通过样本创建,以及训练好的分类器进行人脸检测.实验结果表明:由于充分利用AdaBoost人脸检测方法实时性比较强、检测率高,该方法完全满足Android平台下人脸检测的需要.

关 键 词:人脸检测  分类器  样本创建

A face detection based on AdaBoost algorithm realize on the Android platform
AN Heng-xuan,ZHANG Xue-xi,LI Chao,CHEN Wen-hui,ZOU Bing.A face detection based on AdaBoost algorithm realize on the Android platform[J].Electronic Design Engineering,2014(8):126-130.
Authors:AN Heng-xuan  ZHANG Xue-xi  LI Chao  CHEN Wen-hui  ZOU Bing
Affiliation:1. College ofA utomation Guangdong University of Technology, Guangzhou 510006, China; 2. Beihang University, Beijing 100191, China)
Abstract:Becacuse Android's own face detection algorithm cannot accurately detect the human face, especially wearing glasses can not detect the human face. In this paper, we study a kind of AdaBoost face detection algorithm based on Android system. Firstly, introduce the Android platform of face detection system structure, then account for the AdaBoost face detection module, including eigenvalue , eigenvalue calculation, AdaBoost classifier and set up the development environment. Finally create the sample and the trained classifier for face detection. The experimental results show that: due to take full advantage of AdaBoost face detection method is more real-time, high detection rate, the method is fully meet the needs of the Android platform face detection.
Keywords:face detection  Android  AdaBoost  classifier  create sample
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