Neuronal Specialization for Fine-Grained Distance Estimation using a Real-Time Bio-Inspired Stereo Vision System

Abstract

The human binocular system performs very complex operations in real-time tasks thanks to neuronal specialization and several specialized processing layers. For a classic computer vision system, being able to perform the same operation requires high computational costs that, in many cases, causes it to not work in real time: this is the case regarding distance estimation. This work details the functionality of the biological processing system, as well as the neuromorphic engineering research branch—the main purpose of which is to mimic neuronal processing. A distance estimation system based on the calculation of the binocular disparities with specialized neuron populations is developed. This system is characterized by several tests and executed in a real-time environment. The response of the system proves the similarity between it and human binocular processing. Further, the results show that the implemented system can work in a real-time environment, with a distance estimation error of 15% (8% for the characterization tests).