Neuromorphic Stereo Vision: A Survey of Bio-Inspired Sensors and Algorithms

Author(s)
Lea Steffen, Daniel Reichard, Jakob Weinland, Jacques Kaiser, Arne Roennau, Rüdiger Dillmann
Journal
Frontiers in Neurorobotics
Year
2019
Volume
13
Month
Mai
Abstract
Any visual sensor, whether artificial or biological, maps the 3D-world on a 2D-representation. The missing dimension is depth and most species use stereo vision to recover it. Stereo vision implies multiple perspectives and matching, hence it obtains depth from a pair of images. Algorithms for stereo vision are also used prosperously in robotics. Although, biological systems seem to compute disparities effortless, artificial methods suffer from high energy demands and latency. The crucial part is the correspondence problem; finding the matching points of two images. The development of event-based cameras, inspired by the retina, enables the exploitation of an additional physical constraint – time. Due to their asynchronous course of operation, considering the precise occurrence of spikes, Spiking Neural Networks take advantage of this constraint. In this work, we investigate sensors and algorithms for event-based stereo vision leading to more biologically plausible robots. Hereby, we focus mainly on binocular stereovision.
Online Sources
https://www.frontiersin.org/article/10.3389/fnbot.2019.00028
DOI
10.3389/fnbot.2019.00028
Research focus
Service Robotics and Mobile Manipulation
Project
Human Brain Project, NeuroReact - Echtzeitfähige neuronale Planung für reaktive Industrieroboter
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Published by
Lea Steffen