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

Loading...
Thumbnail Image

Date published

Free to read from

Authors

Xu, Shuoyuan
Savvaris, Al
He, Shaoming
Shin, Hyosang
Tsourdos, Antonios

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Department

Course name

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

Funder/s

Relationships

Relationships

Resources