Car Detection in Aerial Images of Dense Urban Areas

被引：14

作者：

Elmikaty, Mohamed ^{[1
]}

Stathaki, Tania ^{[1
]}

机构：

[1] Imperial Coll London, Dept Elect & Elect Engn, London SW7 2AZ, England

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2018年 / 54卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

VEHICLE DETECTION; RECOGNITION; CLASSIFICATION;

D O I：

10.1109/TAES.2017.2732832

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification subsystems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.

引用

页码：51 / 63

页数：13

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