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A spike-based neuromorphic stereo architecture for active vision


Risi, Nicoletta; Aimar, Alessandro; Donati, Elisa; Solinas, Sergio; Indiveri, Giacomo (2019). A spike-based neuromorphic stereo architecture for active vision. In: ROBUST ARTIFICIAL INTELLIGENCE FOR NEUROROBOTICS, Edinburgh, UK, 26 August 2019 - 28 August 2019.

Abstract

The problem of finding stereo correspondences in binocular vision is solved effortlessly in nature and yet is still a critical bottleneck for artificial machine vision systems. As temporal information is a crucial feature in this process, the advent of event-based vision sensors and dedicated event-based processors promises to offer an effective approach to solve stereo-matching. Indeed, event-based neuromorphic hardware provides an optimal substrate for biologically-inspired, fast, asynchronous computation, that can make explicit use of precise temporal coincidences. Here we present an event-based stereo-vision system that fully leverages the advantages of brain-inspired neuromorphic computing hardware by interfacing event-based vision sensors to an event-based mixed-signal analog/digital neuromorphic processor. We describe the multi-chip sensory-processing setup developed and demonstrate a proof of concept implementation of cooperative stereo-matching that can be used to build brain-inspired active vision systems.

Abstract

The problem of finding stereo correspondences in binocular vision is solved effortlessly in nature and yet is still a critical bottleneck for artificial machine vision systems. As temporal information is a crucial feature in this process, the advent of event-based vision sensors and dedicated event-based processors promises to offer an effective approach to solve stereo-matching. Indeed, event-based neuromorphic hardware provides an optimal substrate for biologically-inspired, fast, asynchronous computation, that can make explicit use of precise temporal coincidences. Here we present an event-based stereo-vision system that fully leverages the advantages of brain-inspired neuromorphic computing hardware by interfacing event-based vision sensors to an event-based mixed-signal analog/digital neuromorphic processor. We describe the multi-chip sensory-processing setup developed and demonstrate a proof of concept implementation of cooperative stereo-matching that can be used to build brain-inspired active vision systems.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:28 August 2019
Deposited On:14 Feb 2020 10:36
Last Modified:15 Feb 2020 17:00
Publisher:s.n.
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://blogs.ed.ac.uk/rai-nr/wp-content/uploads/sites/406/2019/07/RAINR_Risi_etal.pdf

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