The Role of Polarity in Haar-like Features for Face Detection

Human vision is primarily based on local contrast perception and its polarity. Viola and Jones proposed, in their well-known face detector framework, a boosted cascade of weak classifiers based on Haar-like features which encode local contrast and polarity information. Nevertheless contrast polarity invariance, which is not directly modeled in their framework, has been shown to be perceptually relevant for the human capability of detecting faces. In this paper we study, from both algorithmical and perceptual points of view, the effect of enhancing Haar-like features with polarity invariance and how it may improve cascaded classifiers.