Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

This paper presents an asynchronous event-based scheme for automatic intrusion monitoring using Unmanned Aerial Systems (UAS). Event cameras are neuromorphic sensors that capture the illumination changes in the camera pixels with high temporal resolution and dynamic range. In contrast to conventiona...

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Autores principales:	Juan Pablo Rodriguez-Gomez, Augusto Gomez Eguiluz, Jose Ramiro Martinez-De Dios, Anibal Ollero
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Event-based vision intrusion detection surveillance UAV Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/241d571c1b5e4dc69fc60ad70faa11d1
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id	oai:doaj.org-article:241d571c1b5e4dc69fc60ad70faa11d1
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spelling	oai:doaj.org-article:241d571c1b5e4dc69fc60ad70faa11d12021-11-19T00:06:31ZAuto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS2169-353610.1109/ACCESS.2021.3066529https://doaj.org/article/241d571c1b5e4dc69fc60ad70faa11d12021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9380323/https://doaj.org/toc/2169-3536This paper presents an asynchronous event-based scheme for automatic intrusion monitoring using Unmanned Aerial Systems (UAS). Event cameras are neuromorphic sensors that capture the illumination changes in the camera pixels with high temporal resolution and dynamic range. In contrast to conventional frame-based cameras, they are naturally robust against motion blur and lighting conditions, which make them ideal for outdoor aerial robot applications. The presented scheme includes two main perception components. First, an asynchronous event-based processing system efficiently detects intrusions by combining several asynchronous event-based algorithms that exploit the advantages of the sequential nature of the event stream. The second is an off-line training mechanism that adjusts the parameters of the event-based algorithms to a particular surveillance scenario and mission. The proposed perception system was implemented in ROS for on-line execution on board UAS, integrated in an autonomous aerial robot architecture, and extensively validated in challenging scenarios with a wide variety of lighting conditions, including day and night experiments in pitch dark conditions.Juan Pablo Rodriguez-GomezAugusto Gomez EguiluzJose Ramiro Martinez-De DiosAnibal OlleroIEEEarticleEvent-based visionintrusion detectionsurveillanceUAVElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 44840-44854 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Event-based vision intrusion detection surveillance UAV Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Event-based vision intrusion detection surveillance UAV Electrical engineering. Electronics. Nuclear engineering TK1-9971 Juan Pablo Rodriguez-Gomez Augusto Gomez Eguiluz Jose Ramiro Martinez-De Dios Anibal Ollero Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
description	This paper presents an asynchronous event-based scheme for automatic intrusion monitoring using Unmanned Aerial Systems (UAS). Event cameras are neuromorphic sensors that capture the illumination changes in the camera pixels with high temporal resolution and dynamic range. In contrast to conventional frame-based cameras, they are naturally robust against motion blur and lighting conditions, which make them ideal for outdoor aerial robot applications. The presented scheme includes two main perception components. First, an asynchronous event-based processing system efficiently detects intrusions by combining several asynchronous event-based algorithms that exploit the advantages of the sequential nature of the event stream. The second is an off-line training mechanism that adjusts the parameters of the event-based algorithms to a particular surveillance scenario and mission. The proposed perception system was implemented in ROS for on-line execution on board UAS, integrated in an autonomous aerial robot architecture, and extensively validated in challenging scenarios with a wide variety of lighting conditions, including day and night experiments in pitch dark conditions.
format	article
author	Juan Pablo Rodriguez-Gomez Augusto Gomez Eguiluz Jose Ramiro Martinez-De Dios Anibal Ollero
author_facet	Juan Pablo Rodriguez-Gomez Augusto Gomez Eguiluz Jose Ramiro Martinez-De Dios Anibal Ollero
author_sort	Juan Pablo Rodriguez-Gomez
title	Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
title_short	Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
title_full	Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
title_fullStr	Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
title_full_unstemmed	Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
title_sort	auto-tuned event-based perception scheme for intrusion monitoring with uas
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/241d571c1b5e4dc69fc60ad70faa11d1
work_keys_str_mv	AT juanpablorodriguezgomez autotunedeventbasedperceptionschemeforintrusionmonitoringwithuas AT augustogomezeguiluz autotunedeventbasedperceptionschemeforintrusionmonitoringwithuas AT joseramiromartinezdedios autotunedeventbasedperceptionschemeforintrusionmonitoringwithuas AT anibalollero autotunedeventbasedperceptionschemeforintrusionmonitoringwithuas
_version_	1718420598076473344

Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

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