Dual camera based feature for face spoofing detection

Abstract

This paper presents a fused feature using dual cameras for face spoofing detection. The feature takes full advantage of input image pairs in terms of texture and depth. It consists of two parts: 2D component and 3D component. For the former, we propose an algorithm based on image similarity to combine every pair of input images into one graylevel image, from which the 2D feature is extracted. For the latter, based on point feature histograms (PFH) method, we describe the point cloud obtained by stereo reconstruction algorithms. The concatenation of 2D and 3D features above is used to represent the input image pair. Experiments on self collected dataset demonstrate the competitive performance and potential of the proposed feature.