Pursuing 3-D Scene Structures With Optical Satellite Images From Affine Reconstruction to Euclidean Reconstruction

doi:10.1109/TGRS.2022.3213546

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Pursuing 3-D Scene Structures With Optical Satellite Images From Affine Reconstruction to Euclidean Reconstruction
	Wang, Pinhe 1; Shi, Limin2 ; Chen, Bao3 ; Hu, Zhanyi3 ; Qiao, Jianzhong 1; Dong, Qiulei3,4,5
发表期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN	0196-2892
	2022
卷号	60 页码:14
通讯作者	Dong, Qiulei(qldong@nlpr.ia.ac.cn)
摘要	How to use multiple optical satellite images to recover the 3-D scene structure is a challenging and important problem in the remote sensing field. Most existing methods in literature have been explored based on the classical rational polynomial coefficients (RPCs) camera model which requires at least 39 ground control points (GCPs), however, it is nontrivial to obtain such a large number of GCPs in many real scenes. Addressing this problem, we propose a hierarchical reconstruction framework based on multiple optical satellite images, which needs only four GCPs to fully-automated reconstruct the 3-D scene structure. The proposed framework is independent of the RPC model and composed of a dense affine reconstruction stage and a followed affine-to-Euclidean upgrading stage: At the dense affine reconstruction stage, a dense affine reconstruction approach is explored for pursuing the 3-D affine scene structure without any GCP from input satellite images. Then at the affine-to-Euclidean upgrading stage, the obtained 3-D affine structure is upgraded to a Euclidean one with four GCPs. Experimental results on two public datasets demonstrate that the proposed method significantly outperforms several state-of-the-art methods in most cases.
关键词	Satellites Image reconstruction Cameras Three-dimensional displays Solid modeling Optical sensors Optical imaging Affine-to-Euclidean upgrading dense affine reconstruction ground control points (GCPs) hierarchical reconstruction optical satellite image
DOI	10.1109/TGRS.2022.3213546
关键词[WOS]	DIGITAL ELEVATION MODELS ; STEREO
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[U1805264] ; National Natural Science Foundation of China[61991423] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32050100] ; Beijing Municipal Science and Technology Project[Z211100011021004]
项目资助者	National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000875938400004
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50548
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习多模态人工智能系统全国重点实验室_机器人视觉
通讯作者	Dong, Qiulei
作者单位	1.Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110169, Peoples R China 2.Chinese Acad Sci, Res Ctr Aerosp Informat, Inst Automat, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 110190, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technolog, Beijing 100190, Peoples R China
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Wang, Pinhe,Shi, Limin,Chen, Bao,et al. Pursuing 3-D Scene Structures With Optical Satellite Images From Affine Reconstruction to Euclidean Reconstruction[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:14.
APA	Wang, Pinhe,Shi, Limin,Chen, Bao,Hu, Zhanyi,Qiao, Jianzhong,&Dong, Qiulei.(2022).Pursuing 3-D Scene Structures With Optical Satellite Images From Affine Reconstruction to Euclidean Reconstruction.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,14.
MLA	Wang, Pinhe,et al."Pursuing 3-D Scene Structures With Optical Satellite Images From Affine Reconstruction to Euclidean Reconstruction".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):14.