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dc.creatorRodríguez Gómez, Juan Pabloes
dc.creatorEguiluz, Augusto Gómezes
dc.creatorMartínez de Dios, José Ramiroes
dc.creatorOllero Baturone, Aníbales
dc.date.accessioned2022-09-05T16:30:17Z
dc.date.available2022-09-05T16:30:17Z
dc.date.issued2021
dc.identifier.citationRodríguez Gómez, J.P., Eguiluz, A.G., Martínez de Dios, J.R. y Ollero, A. (2021). Auto-tuned event-based perception scheme for intrusion monitoring with UAS. IEEE Access, 9 (Article number 9380323), 44840-44854.
dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/11441/136744
dc.descriptionArticle number 9380323es
dc.description.abstractThis 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.es
dc.description.sponsorshipMinisterio de Ciencia e Innovación DPI2017-89790-Res
dc.description.sponsorshipComisión Europea H2020-2019-871479es
dc.description.sponsorshipConsejo Europeo de Investigación 788247es
dc.formatapplication/pdfes
dc.format.extent15 p.es
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineers Inc.es
dc.relation.ispartofIEEE Access, 9 (Article number 9380323), 44840-44854.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEvent-based visiones
dc.subjectIntrusion detectiones
dc.subjectSurveillancees
dc.subjectUAVes
dc.titleAuto-tuned event-based perception scheme for intrusion monitoring with UASes
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.relation.projectIDDPI2017-89790-Res
dc.relation.projectIDH2020-2019-871479es
dc.relation.projectID788247es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/abstract/document/9380323es
dc.identifier.doi10.1109/ACCESS.2021.3066529es
dc.journaltitleIEEE Accesses
dc.publication.volumen9es
dc.publication.issueArticle number 9380323es
dc.publication.initialPage44840es
dc.publication.endPage44854es

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as: Attribution-NonCommercial-NoDerivatives 4.0 Internacional