YOLO+JPDA在小型无人机多目标跟踪中的实时实现

2018 International Conference on Unmanned Aircraft Systems (ICUAS) Pub Date : 2018-06-01 DOI:10.1109/ICUAS.2018.8453398

Shuoyuan Xu, A. Savvaris, Shaoming He, Hyo-Sang Shin, A. Tsourdos

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引用次数: 27

摘要

本文介绍了一种小型无人机实时多目标检测与跟踪系统的研制。选择并实现了YOLO深度学习视觉目标检测算法和JPDA多目标检测算法。介绍了这些算法的原理和实现细节。在公共数据集和无人机航拍视频上对系统进行了性能分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2018 International Conference on Unmanned Aircraft Systems (ICUAS)

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