A Blur-Robust Descriptor with Applications to Face Recognition

—Understanding the effect of blur is an important problem in unconstrained visual analysis. We address this problem in the context of image-based recognition, by a fusion of image-formation models, and differential geometric tools. First, we discuss the space spanned by blurred versions of an image and then under certain assumptions, provide a differential geometric analysis of that space. More specifically, we create a subspace resulting from convolution of an image with a complete set of orthonormal basis functions of a pre-specified maximum size (that can represent an arbitrary blur kernel within that size), and show that the corresponding subspaces created from a clean image and its blurred versions are equal under the ideal case of zero noise, and some assumptions on the properties of blur kernels. We then study the practical utility of this subspace representation for the problem of direct recognition of blurred faces, by viewing the subspaces as points on the Grassmann manif...

• Type: Journal
• Year: 2012
• Where: PAMI
• Authors: Raghuraman Gopalan, Sima Taheri, Pavan K. Turaga, Rama Chellappa
• Keywords: Geometric Tools, Grassmann Manifold, PAMI 2012, Software Engineering, Zero Noise