Face detection and facial feature extraction using support vector machines

Proposes a fast algorithm for detecting human face and extracting the facial features. For this task, we have developed a flexible coordinate system and several support vector machines. The design of a face model for both detection and extraction is based on multi-resolution wavelet decomposition (MWD). Using a mean face, the MWD and a small number of feature points are applied for rough searching by estimating the modified cross correlation (MCC). More accurate results can be achieved by a serious of support vector machines (SVMs). Experimental results show that the proposed approach is fast and has a high detection rate even in cases when a face is embedded in a complicated background.