Vision-based UAVs Aerial Image Localization: A Survey

被引:26
|
作者
Xu, Yingxiao [1 ]
Pan, Long [2 ]
Du, Chun [1 ]
Li, Jun [1 ]
Jing, Ning [1 ]
Wu, Jiangjiang [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect Sci, Changsha, Peoples R China
[2] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha, Peoples R China
来源
PROCEEDINGS OF THE 2ND ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON AI FOR GEOGRAPHIC KNOWLEDGE DISCOVERY (GEOAI 2018) | 2018年
关键词
UAVs Aerial Image; Vision-based Image Localization; Image Description; Semantic; Deep Learning; FAB-MAP; CLASSIFICATION; FEATURES; SCALE; WORDS; SLAM;
D O I
10.1145/3281548.3281556
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Unmanned aerial vehicles (UAVs) have been increasingly used in earth observation, public safety, military and civilian applications due to its portability, high mobility and flexibility. In some GPS-denied environments, accurate drone position cannot be obtained due to occlusion, multi-path interference and other factors. While understanding and localization the content of the images is vital for earth observation, map revision, multi-source image fusion, disaster relief, smart city and other applications. The progress of computer vision and convolutional neural networks(CNNs) in image processing provide a promising solution to locate UAVs aerial image and mapping to the large-scale reference image. Firstly, key localization techniques based on image retrieval- image description, image matching and position mapping are summarized considering the characteristics of UAVs aerial images. And then, image localization based on extracting deep semantic features and image localization based on classification method by subdividing areas are recommended. Throughout this paper, we will have an insight into the prospect of the UAVs image localization and the challenges to be faced.
引用
收藏
页码:9 / 18
页数:10
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