Two-stage classification using selective attention for fast face detection

A novel system for face detection in images and video sequences is presented. The system incorporates a two-stage linear discriminant and nonlinear support vector machine classifier coupled with a front-end biologically-inspired search scheme. Results based on the CMU test set demonstrate that by using such a classifier arrangement with a non-exhaustive searching scheme, a significant reduction in computational complexity is achieved while maintaining comparable accuracy to other leading face detection systems.