Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6957
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dc.contributor.authorLezki, Hazal-
dc.contributor.authorÖztürk, I. Ahu-
dc.contributor.authorAkpınar, M. Akif-
dc.contributor.authorYücel, M. Kerim-
dc.contributor.authorLogoğlu, K. Berker-
dc.contributor.authorErdem, Aykut-
dc.contributor.authorErdem, Erkut-
dc.date.accessioned2021-09-11T15:44:31Z-
dc.date.available2021-09-11T15:44:31Z-
dc.date.issued2019en_US
dc.identifier.citation15th European Conference on Computer Vision (ECCV) -- SEP 08-14, 2018 -- Munich, GERMANYen_US
dc.identifier.isbn978-3-030-11012-3; 978-3-030-11011-6-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://doi.org/10.1007/978-3-030-11012-3_8-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6957-
dc.description.abstractMoving object detection is an imperative task in computer vision, where it is primarily used for surveillance applications. With the increasing availability of low-altitude aerial vehicles, new challenges for moving object detection have surfaced, both for academia and industry. In this paper, we propose a new approach that can detect moving objects efficiently and handle parallax cases. By introducing sparse flow based parallax handling and downscale processing, we push the boundaries of real-time performance with 16 FPS on limited embedded resources (a five-fold improvement over existing baselines), while managing to perform comparably or even improve the state-of-the-art in two different datasets. We also present a roadmap for extending our approach to exploit multi-modal data in order to mitigate the need for parameter tuning.en_US
dc.language.isoenen_US
dc.publisherSpringer International Publishing Agen_US
dc.relation.ispartofComputer Vision - Eccv 2018 Workshops, Pt Iien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMoving object detectionen_US
dc.subjectOptical flowen_US
dc.subjectUAVen_US
dc.subjectDronesen_US
dc.subjectEmbedded visionen_US
dc.subjectReal-time visionen_US
dc.titleJoint Exploitation of Features and Optical Flow for Real-Time Moving Object Detection on Dronesen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesLecture Notes in Computer Scienceen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume11130en_US
dc.identifier.startpage100en_US
dc.identifier.endpage116en_US
dc.authorid0000-0002-6744-8614-
dc.authorid0000-0002-6280-8422-
dc.identifier.wosWOS:000594380500008en_US
dc.identifier.scopus2-s2.0-85061774580en_US
dc.institutionauthorLezki, Hazal-
dc.identifier.doi10.1007/978-3-030-11012-3_8-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference15th European Conference on Computer Vision (ECCV)en_US
dc.identifier.scopusqualityQ2-
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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