Fast face detection by lifting dyadic wavelet filters

This paper presents a fast algorithm for detecting facial parts such as nose, eyes and lips in an image by using lifting dyadic wavelet filters. Free parameters in the lifting filters are learned so as to maximize the cosine of an angle between a vector whose components are the lifting filters and a vector of pixels in the facial part. Applying the learned filter to a test image, facial parts in the image is detected. In simulation, we show that our algorithm is fast and robust one for detecting facial parts from an image.