Applying scattering operators for face recognition: A comparative study

Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background, expression, hairstyle, and glasses. Thus, a powerful feature descriptor with local-deformation tolerance ability and discriminating capability is essential to fulfill all these variations. In this paper, we present a local descriptor, scattering operator, which includes multi-scale and multi-direction co-occurrence information. It is computed with a cascade of wavelet decompositions and complex modulus. This scattering representation is locally translation invariant and can linearize deformations. We evaluate the abilities of this Gabor-based scattering operator by an effective face recognition paradigm and show that this descriptor outperforms the compared descriptors.