Top-Down Facilitation of Multistage Decisions for Face Recognition

Visual processing in humans is, without a doubt, far superior that that in machines, especially when the end goal is object or face recognition. Neural results from visual object and face recognition in humans provide an excellent model for developing better techniques in machine vision. In this paper, the authors present a particular neural result pertaining to the use of Low Spatial Frequency (LSF) imagery to facilitate recognition of High Spatial Frequency (HSF) representations of faces and objects and apply it first as a general technique for the classification problem and second as a high-performance recognition method to deal with face recognition on blurry imagery.