Combined approach to face detection for biometric identification systems

The paper describes combined approach to face detection for grayscale images using the combined cascade of neural network classifiers which consists of Haar-like features' cascade of weak classifiers and convolutional neural network. The combined cascade with proposed face candidates' verification method allows achieving one of the best detection rates on CMU test set and a high processing speed suitable for a video flow processing. In the last stage of our algorithm we provide extraction of salient facial features for pose estimation and recognition.