关键词: 人脸检测, 协方差特征, Adaboost方法, 特征提取

Abstract: Face detection method based on the cascade architecture using harr-like feature has high detection rate and rapid detection speed.But harr-like feature is sensitive for edge and lines and can describe given direction.Combining cascade decision-making technology，the face detection method based on boosting covariance features is presented.Firstly，the covariance features are figured out.And then，the weak detectors are constructed using those features.Finally，utilizing the Adaboost algorithm to combine these decision results from the weak detectors，the face images are filtered through the waterfall cascade architecture.Consequently，the final decision outcome are gained.The experimental results testify the detector has anti-noise power.The detection rate is higher than the former methods based on the cascade architecture using harr-like feature obviously.

Key words: face detection, covariance feature, Adaboost, feature extraction