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In order to effectively solve the location of acquisition device is not ideal,collected face image is not positive,and cause false detection and error detection. First,the principal component analysis (PCA) and the Scale Invariant Feature Transform (SIFT) algorithm combined,respectively rotary dimensionality reduction and SIFT algorithm PCA algorithm,pan,zoom,and quickly rotating part affine invariant face early detection. Then,using the facial features of a human face human face correction and calibration,improve face detection accuracy. Finally,the improved algorithm AdaBoost face classifier training and match rate calculation of key points,complete and accurate detection of the rotation face. The results showed that:compared with the traditional method false detection rate was significantly reduced, at the same time ensure a high detection rate.