一种基于Adaboost算法的人脸检测  

Face Detection Based on AdaBoost Algorithm

作　　者：刘欢喜[1] 刘允才[1] 

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《上海交通大学学报》2008年第7期1119-1123,共5页Journal of Shanghai Jiaotong University

基　　金：国家重点基础研究发展规划(973)项目(2006CB303103)

摘　　要：针对经典Adaboost算法存在训练速度缓慢、检测结果过分依赖训练样本集的现象,提出一种改进的人脸检测算法.该算法在原有Adaboost算法的基础上,利用特征约简来提高训练速度,引入样本扩张、多分辨率搜索等策略来提高检测效率.算法还在一定程度上解决了遮挡、旋转、光照对人脸检测带来的影响等问题.实验结果表明:该方法具有较快的训练速度和良好的检测性能.The algorithm of face detection based on Adaboost is an aggressive learning algorithm, which is capable of processing images rapidly while having high detection rates. However, the algorithm has some deficiencies： the speed of training is rather slow, and the quality of the final detection depends highly on the consistence of the training set. A novel method based on Adaboost algorithm for face detection was presented in the following ways, such as, the feature reducing is applied to accelerate the pace of training, many strategies including samples augmenting and multi resolution searching are used to improve the performance of detecting. The problem about effect of shelter, rotation and illumination on face detection can hence be solved to some extent. The experimental results show the proposed approach improves both the training speed and the detection efficiency.

关 键 词：ADABOOST算法 人脸检测 特征约简 样本扩张 多分辨率搜索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]