Real-time implementation of YOLO+JPDA for small scale UAV multiple object tracking

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dc.contributor.authorXu, Shuoyuan
dc.contributor.authorSavvaris, Al
dc.contributor.authorHe, Shaoming
dc.contributor.authorShin, Hyosang
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2019-03-07T15:31:34Z
dc.date.available2019-03-07T15:31:34Z
dc.date.issued2018-09-03
dc.description.abstractThis paper describes the development of a real-time multiple object detection and tracking system for a small scale UAV. The YOLO deep learning visual object detection algorithm and JPDA multiple target detection algorithm, were selected and implemented. The theory and implementation details of these algorithms are presented. The performance analysis of the system is done on both public dataset and aerial videos taken by UAV.en_UK
dc.identifier.citationXu S, Savvaris A, He S, Shin H-S and Tsourdos A., Real-time implementation of YOLO+JPDA for small scale UAV multiple object tracking. In: 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas, 12-15 June 2018.en_UK
dc.identifier.isbn978-1-5386-1355-9
dc.identifier.issn2575-7296
dc.identifier.urihttps://doi.org/10.1109/ICUAS.2018.8453398
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/13970
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectObject detectionen_UK
dc.subjectCurrent measurementen_UK
dc.subjectTarget trackingen_UK
dc.subjectReal-time systemsen_UK
dc.subjectObject trackingen_UK
dc.subjectUnmanned aerial vehiclesen_UK
dc.subjectEstimationen_UK
dc.titleReal-time implementation of YOLO+JPDA for small scale UAV multiple object trackingen_UK
dc.typeConference paperen_UK

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