Fast Face Detection Using QuadTree Based Color Analysis and Support Vector Verification

Shu-Fai Wong, Kwan-Yee Kenneth Wong

Abstract: Face detection has potential applications in a wide range of commercial products such as automatic face recognition system. Commonly used face detection algorithms can extract faces from images accurately and reliably, but they often take a long time to finish the detection process. Recently, there is an increasing demand of real time face detection algorithm in applications like video surveillance system. This paper aims at proposing a multi-scale face detection scheme using Quadtree so that the time complexity of the face detection process can be reduced. By performing analysis from coarse to fine scales, the proposed scheme uses skin color as a heuristic feature, and support vector machine as a verification tool to detect face. Experimental results show that the proposed scheme can detect faces from images reliably and quickly.