Perception Based Lighting Balance for Face Detection

Abstract

For robust face detection, lighting is considered as one of the greatest challenges. The three-step face detection framework provides a practical method for real-time face detection. In this framework, the last step can employ computation extensive method to remove the false alarm and usually some de-lighting methods are done. It is complex to model the lighting variance precisely. The usually used simplified lighting model fails under non-uniform lighting conditions for the reason that it cannot account for the cast shadow, shading, and highlight, which are the main variances caused by non-uniform lighting. According to the adaptation capacity of the human vision system, we propose a perception based mapping method (PMM) to balance the influence of non-uniform lighting. Experimental results indicate that with PMM as the lighting-filter the false positives caused by lighting variance can be removed more accurately in the face detection tasks. PMM shows its outstanding performance especially under the extreme lighting conditions.