Comparing the performance of single-layer and two-layer support vector machines on face detection
Ji Han, Peter C. R. Lane, Nicolas A.C. Davey, Yi Sun · University of Hertfordshire Research Archive (University of Hertfordshire) · 2007
Face detection is a vibrant research branch of computer vision.Methods of detecting faces fall into two categories: global and component-based.In this paper, we compare these two approaches by applying a single-layer and a dual-layer support vector machine classifier to detect faces from images.Experiments suggest that the single-layer classifier has better performance on detecting faces with big attitude extremity.But the dual-layer classifier has equivalent performance on detecting frontal faces and has more generality on different databases.