Real-time Implementation of YOLO+JPDA for Small Scale UAV Multiple Object Tracking

Shuoyuan Xu, Al Savvaris, Shaoming He, Hyo Sang Shin, Antonios Tsourdos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

44 Citations (Scopus)

Abstract

This 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.

Original languageEnglish
Title of host publication2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1336-1341
Number of pages6
ISBN (Print)9781538613535
DOIs
Publication statusPublished - 31 Aug 2018
Externally publishedYes
Event2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018 - Dallas, United States
Duration: 12 Jun 201815 Jun 2018

Publication series

Name2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018

Conference

Conference2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
Country/TerritoryUnited States
CityDallas
Period12/06/1815/06/18

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