Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration

doi:10.1016/j.displa.2023.102615

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration
	Zhao, Yuehua 1,2; Zhang, Jiguang 3; Xu, Shibiao 2; Ma, Jie 1; Wang, Huishan 1
刊名	DISPLAYS
	2024
卷号	81 页码:8
关键词	Point cloud registration Low overlap Reliable correspondences Geometric-and-semantic consistency
ISSN号	0141-9382
DOI	10.1016/j.displa.2023.102615
通讯作者	Xu, Shibiao(shibiaoxu@bupt.edu.cn) ; Ma, Jie(jma@hebut.edu.cn)
英文摘要	The presence of partial or low overlaps in real point cloud pairs poses significant challenges to obtain robust registration. There is an absence of a unified framework that localizes reliable overlapping regions and correspondences. This work proposes an adaptive point cloud geometric encoding network based on semantic enhancement that generates overlap information with geometric-and-semantic consistency in various scenarios. This enables the network to further ensure distinctive geometric representation when the low overlap point cloud pairs have scarce differences in the geometric structures. In addition, our study includes experiments conducted on a self-created semantic-assisted dataset designed to facilitate in-depth research on point cloud registration. The experimental results clearly demonstrate the efficacy and overall improvements of the registration performance, particularly highlighting the potential of our approach in addressing the challenges associated with low overlap scenarios that have repetitive geometry patterns.
资助项目	Beijing Natural Science Foundation[JQ23014] ; National Natural Science Foundation of China[62271074] ; National Natural Science Foundation of China[62171321] ; National Natural Science Foundation of China[62162044] ; National Natural Science Foundation of China[52175493] ; National Natural Science Foundation of China[32271983] ; Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University[VRLAB2023B01]
WOS研究方向	Computer Science ; Engineering ; Instruments & Instrumentation ; Optics
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:001142538000001
资助机构	Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54853]
专题	多模态人工智能系统全国重点实验室
通讯作者	Xu, Shibiao; Ma, Jie
作者单位	1.Hebei Univ Technol, Sch Elect & Informat Engn, Tianjin 30401, Peoples R China 2.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100090, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Yuehua,Zhang, Jiguang,Xu, Shibiao,et al. Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration[J]. DISPLAYS,2024,81:8.
APA	Zhao, Yuehua,Zhang, Jiguang,Xu, Shibiao,Ma, Jie,&Wang, Huishan.(2024).Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration.DISPLAYS,81,8.
MLA	Zhao, Yuehua,et al."Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration".DISPLAYS 81(2024):8.