dc.creator | Rodríguez Gómez, Juan Pablo | es |
dc.creator | Eguiluz, Augusto Gómez | es |
dc.creator | Martínez de Dios, José Ramiro | es |
dc.creator | Ollero Baturone, Aníbal | es |
dc.date.accessioned | 2022-09-05T16:30:17Z | |
dc.date.available | 2022-09-05T16:30:17Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Rodríguez 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.issn | 2169-3536 | es |
dc.identifier.uri | https://hdl.handle.net/11441/136744 | |
dc.description | Article number 9380323 | es |
dc.description.abstract | 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. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación DPI2017-89790-R | es |
dc.description.sponsorship | Comisión Europea H2020-2019-871479 | es |
dc.description.sponsorship | Consejo Europeo de Investigación 788247 | es |
dc.format | application/pdf | es |
dc.format.extent | 15 p. | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | es |
dc.relation.ispartof | IEEE Access, 9 (Article number 9380323), 44840-44854. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Event-based vision | es |
dc.subject | Intrusion detection | es |
dc.subject | Surveillance | es |
dc.subject | UAV | es |
dc.title | Auto-tuned event-based perception scheme for intrusion monitoring with UAS | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.projectID | DPI2017-89790-R | es |
dc.relation.projectID | H2020-2019-871479 | es |
dc.relation.projectID | 788247 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/abstract/document/9380323 | es |
dc.identifier.doi | 10.1109/ACCESS.2021.3066529 | es |
dc.journaltitle | IEEE Access | es |
dc.publication.volumen | 9 | es |
dc.publication.issue | Article number 9380323 | es |
dc.publication.initialPage | 44840 | es |
dc.publication.endPage | 44854 | es |