A Real-time Approach for Autonomous Detection and Tracking of Moving Objects from UAV

被引：0

作者：

Sadeghi-Tehran, Pouria ^{[1
]}

Clarke, Christopher ^{[1
]}

Angelov, Plamen ^{[1
]}

机构：

[1] Univ Lancaster, Sch Comp & Commun, Intelligent Syst Lab, Data Sci Grp, Lancaster LA1 4YW, England

来源：

2014 IEEE SYMPOSIUM ON EVOLVING AND AUTONOMOUS LEARNING SYSTEMS (EALS) | 2014年

关键词：

autonomous object detection; mobile visual surveillance platform; UAV;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken from a real UAV and the evaluation results are demonstrated in this paper.

引用

页码：43 / 49

页数：7

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