MBLBP face detection with multi-exit Asymmetric Boosting

Abstract

Face detection plays an important role in many applications such as video surveillance, face recognition, face image database management etc. This paper presents a new technique which reduces the learning and detection time using the multi block local binary pattern (MBLBP) with Multi-exit Asymmetric Boosting. In this technique, the selected features are reduced by around 1/20 of Haar-like method so the learning time is also reduced by about 1/20. The detection time is also reduced by more than 1/4 of Haar-like detector. Multi-exit Asymmetric Boosting reduces features by about 1/5 of the cascade method so the learning and detection time is also reduced.