吉林大学学报（理学版）2018，Vol.56Issue(3)：610-616,7.DOI:10.13413/j.cnki.jdxblxb.2018.03.24
基于多纹理CS-LBP特征的 多视角人脸检测算法
Multi-view Face Detection Algorithm Based on Multi-texture CS-LBP Features
摘要
Abstract
We proposed a multi-texture centrosymmetric local binary pattern (CS-LBP ) feature to realize multi-view face detection in complex environments .The feature retained the characteristics of Haar ordinal relations ,so we drew on the experience of the combination of local binary pattern (LBP) to extract features from four texture directions ,such as horizontal ,vertical ,+45° and -45° ,so as to ensure the robustness of face detection in direction ,illumination ,rotation and so on .The algorithm adopted the cascade architecture .First ,face images were partitioned according to different angles of view ,and multi-texture features were extracted respectively .Then some independent classifiers were designed to eliminate the non-face window step by step .Finally ,the multilayer perceptron (MLP)was used to synthesize the detection effect of each angle of view to output the detection results .The results of verification experiments on data sets FDDB and CM U PIE show that this method is effective for multi-view face detection in complex environment .Compared with traditional convolution neural network face detection method ,this method has higher accuracy .关键词
人脸检测/积分图/多纹理中心对称局部二值模式/级联结构Key words
face detection/integration graph/multi-texture centrosymmetric local binary pattern/cascade architecture分类
信息技术与安全科学引用本文复制引用
崔凯,才华,陈广秋,谷欣超,孙俊喜..基于多纹理CS-LBP特征的 多视角人脸检测算法[J].吉林大学学报（理学版）,2018,56(3):610-616,7.基金项目
国家自然科学基金(批准号:61172111)、吉林省科技发展计划项目(批准号:20160101260JC)和吉林省教育厅"十三五"科学技术研究项目(批准号:JJKH20170625KJ). （批准号:61172111）
