摘要
提出了一种基于二维离散小波变换的人脸检测算法.该算法采用Haar小波计算小波脸,导出了提取人脸特征向量的相应公式,利用感知准则训练线性分类器进行分类判决.在4个不同的人脸数据集上与特征脸方法进行了比较.结果表明,该算法的计算效率和检测精度均优于特征脸方法.
A novel algorithm based on two-dimensional discrete wavelet transform for frontal face detection was presented. The algorithm calculated waveletfaces by using Haar wavelet, deduced corresponding formulation for face feature extraction, and used perceptron algorithm to train linear classifier for classification. The comparison between the proposed approach and Eigenfaces method was carried out on four different face data sets. The results show that the computational efficiency and detection accuracy of the proposed algorithm is superior to Eigenfaces method.
出处
《北京邮电大学学报》
EI
CAS
CSCD
北大核心
2006年第3期114-117,共4页
Journal of Beijing University of Posts and Telecommunications
基金
国家自然科学基金项目(60475007)
教育部重点基金项目(02029)
教育部跨世纪人才基金项目
重庆市科委基金基目
重庆市教委基金项目
关键词
人脸检测
离散小波变换
小波脸
face detection
discrete wavelet transform
waveletfaces
