In view of the poor robustness of existing face detection algorithms,a new face detection algorithm based on fa-cial physiological signals is proposed in this paper. First,remote photoplethysmography is used to extract facial physiological signals caused by heart beats from facial images. After that,the original facial signal is denoised by band-pass filtering,and then the signal is converted to frequency domain by fast Fourier transform to extract new spectral features. Finally,machine learning model is used to realize binary classification and distinguish real faces from false faces. The results show that on Replay-Attack database,the best accuracy rate is 99.15％ against two types of fraud attacks:print and screen display. The algorithm shows excellent performance in the screen attack scenario,which lays a solid foundation for further deepening the research of face anti-fraud algorithm.
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