Real-time implementation of YOLO+JPDA for small scale UAV multiple object tracking
Date
2018-09-03
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Supervisor/s
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Department
Type
Conference paper
ISSN
2575-7296
Format
Citation
Xu 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.
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.
Description
Software Description
Software Language
Github
Keywords
Object detection, Current measurement, Target tracking, Real-time systems, Object tracking, Unmanned aerial vehicles, Estimation
DOI
Rights
Attribution-NonCommercial 4.0 International