Hybrid face detection system with robust face and non-face discriminability
Nacer Farajzadeh, Karim Faez · 2008
While the face detection algorithm proposed by Viola and Jones has enough detection speed in still or video images and is applicable in practical applications, it is not reliable yet. That is, the number of false positives increases as background complexity increases. And sometimes it reports false positives, even for simple backgrounds. This problem can get the automatic face recognition systems (AFRSs) into trouble. In this paper, a hybrid system for face detection is introduced concerning itpsilas applicability in real world applications. Our approach is based on Viola and Jonespsilas work and uses Radial Basis Neural Network (RBFNN). The main characteristic of our approach is its robust face and non-face discriminability. Due to the extensive experiments, it is shown that the proposed system has decreased about 90% of false positives reported by the Viola and Jones algorithm.