太赫兹科学与电子信息学报Issue(2)：272-278,7.DOI:10.11805/TKYDA201502.0272
基于差分特征的多视角人脸检测
Differential features based multi-view face detection
摘要
Abstract
Pose and illumination variations are two major challenges in face detection. Therefore,a novel face detection method based on differential features is proposed. This method extracts first order and second order differential features from images, which are respectively used to train two face detectors using the Gentle Adaboost algorithm with the Classification And Regression Trees(CART) as weak classifiers. Given a new image, the two face detectors are first separately applied to detect candidate faces in the image, and then their detected face regions are combined to give the final face detection results. Thanks to the illumination invariance of first order derivative features and to the rotation invariance of second order derivative features, the proposed differential features based face detection method can better handle the detection of multi-view faces in complex background. The proposed method has been evaluated on the CMU-MIT and FDDB datasets and the results demonstrate its effectiveness.关键词
人脸检测/差分特征/Gentle Adaboost算法/分类与回归树/融合Key words
face detection/differential features/Gentle Adaboost/Classification And Regression Trees/fusion分类
信息技术与安全科学引用本文复制引用
杨智宇,吴志红,赵启军,张艺衡..基于差分特征的多视角人脸检测[J].太赫兹科学与电子信息学报,2015,(2):272-278,7.基金项目
国家自然科学基金资助项目(NO.61202161,61202160)；科技部重大仪器专项资助项目(2013YQ49087904) （NO.61202161,61202160）
