The Human Visual Cortex: Universal Feature Descriptors and Object Recognition with the GPU
Abstract

A biologically motivated method of extracting image features is presented and compared to existing techniques, both of biological motivation and otherwise.  Image features are computed using Gabor filterbanks.  A series of image processing modules are presented with application to object recognition, motion estimation and depth maps to demonstrate the universal nature of the features extracted.  This type of processing covers both main pathways in the Human Visual Cortex.  The functionality of each module directly maps to an associated region of the Human Visual Cortex and the processing done in each module corresponds to the processing known to be done in that region of the brain, as measured by Functional Magnetic Resonsance Imaging (fMRI) studies.  This work also abstracts the modern Graphic Processing Unit (GPU) for biological image processing.  This is done primarily in the form of SIMD image processing using OpenGL and demonstrates a noteworthy speedup over the SISD equivalent.