NeuroDSP Accelerator for Face Detection Application

Abstract

Neuro-Inspired Vision approach, based on models from biology, allows to reduce the computational complexity. One of these models - The Hmax model - shows that the recognition of an object in the visual cortex mobilizes V1, V2 and V4 areas. From the computational point of view, V1 corresponds to the area of the directional filters (for example Gabor filters or wavelet filters). This information is then processed in the area V2 in order to obtain local maxima. This new information is then sent to an artificial neural network. This neural processing module corresponds to area V4 of the visual cortex and is intended to categorize objects present in the scene. In order to realize autonomous vision systems (low-power consumption) with such treatments inside, we studied a new architeure of a Neural Processor named NeuroDSP. We describe in this paper an optimized Hmax model implementation on this Neural Processor for a face detection application.