Face Detection using DT-CWT on Spectral Histogram

A method using DT-CWT spectral histograms and support vector machine (SVM) for face detection is proposed in this paper. In this face detection method, dual tree complex wavelets transform (DT-CWT) filter is used instead of Gabor filter. DT-CWT is a novel wavelet transform recently studied, which provides good directional selectivity in six different fixed orientations at different scales. It has limited redundancy for images and is much faster than Gabor transform to compute. Experimental results show that DT-CWT is a proper candidate to replace Gabor transform in face detection based on spectral histograms. By using an SVM trained on a set of 4000 faces aligned and 6000 non-face images produced by bootstrap algorithm, a robust classifying function for face and non-face pattern is obtained. The preliminary experimental results show that DT-CWT applied in face detection gives the satisfying performance. Several further improvements in computation time and performance are discussed