Rodyti trumpą aprašą

dc.contributor.authorFurmonas, Justas
dc.contributor.authorLiobe, John Charles
dc.contributor.authorBarzdėnas, Vaidotas
dc.date.accessioned2023-09-18T16:12:16Z
dc.date.available2023-09-18T16:12:16Z
dc.date.issued2022
dc.identifier.issn1424-8220
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112328
dc.description.abstractEvent-based cameras have increasingly become more commonplace in the commercial space as the performance of these cameras has also continued to increase to the degree where they can exponentially outperform their frame-based counterparts in many applications. However, instantiations of event-based cameras for depth estimation are sparse. After a short introduction detailing the salient differences and features of an event-based camera compared to that of a traditional, frame-based one, this work summarizes the published event-based methods and systems known to date. An analytical review of these methods and systems is performed, justifying the conclusions drawn. This work is concluded with insights and recommendations for further development in the field of event-based camera depth estimation.eng
dc.formatPDF
dc.format.extentp. 1-26
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyCABI (abstracts)
dc.relation.isreferencedbyGale's Academic OneFile
dc.source.urihttps://www.mdpi.com/1424-8220/22/3/1201
dc.titleAnalytical review of event-based camera depth estimation methods and systems
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license https://creativecommons.org/licenses/by/4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references66
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyElektronikos fakultetas / Faculty of Electronics
dc.subject.researchfieldT 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering
dc.subject.studydirectionE09 - Elektronikos inžinerija / Electronic engineering
dc.subject.vgtuprioritizedfieldsIK0202 - Išmaniosios signalų apdorojimo ir ryšių technologijos / Smart Signal Processing and Telecommunication Technologies
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enevent-based camera
dc.subject.enneuromorphic
dc.subject.endepth estimation
dc.subject.enmonocular
dcterms.sourcetitleSensors
dc.description.issueiss. 3
dc.description.volumevol. 22
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000755485800001
dc.identifier.doi10.3390/s22031201
dc.identifier.elaba118606870


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