Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration

doi:10.3390/rs13152868

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration
	Tian, Yonglin1,2 ; Wang, Xiao2,3 ; Shen, Yu2,4 ; Guo, Zhongzheng 2; Wang, Zilei 1; Wang, Fei-Yue2,3
发表期刊	REMOTE SENSING
	2021-08-01
卷号	13 期号:15 页码:17
通讯作者	Wang, Xiao(x.wang@ia.ac.cn)
摘要	Three-dimensional information perception from point clouds is of vital importance for improving the ability of machines to understand the world, especially for autonomous driving and unmanned aerial vehicles. Data annotation for point clouds is one of the most challenging and costly tasks. In this paper, we propose a closed-loop and virtual-real interactive point cloud generation and model-upgrading framework called Parallel Point Clouds (PPCs). To our best knowledge, this is the first time that the training model has been changed from an open-loop to a closed-loop mechanism. The feedback from the evaluation results is used to update the training dataset, benefiting from the flexibility of artificial scenes. Under the framework, a point-based LiDAR simulation model is proposed, which greatly simplifies the scanning operation. Besides, a group-based placing method is put forward to integrate hybrid point clouds, via locating candidate positions for virtual objects in real scenes. Taking advantage of the CAD models and mobile LiDAR devices, two hybrid point cloud datasets, i.e., ShapeKITTI and MobilePointClouds, are built for 3D detection tasks. With almost zero labor cost on data annotation for newly added objects, the models (PointPillars) trained with ShapeKITTI and MobilePointClouds achieved 78.6% and 60.0% of the average precision of the model trained with real data on 3D detection, respectively.
关键词	virtual LiDAR hybrid point clouds virtual-real interaction 3D detection
DOI	10.3390/rs13152868
关键词[WOS]	SYSTEMS ; VISION
收录类别	SCI
语种	英语
资助项目	State Key Program of the National Natural Science Foundation of China[61533019] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) ; National Natural Science Foundation of China[U1811463] ; Key Research and Development Program of Guangzhou[202007050002]
项目资助者	State Key Program of the National Natural Science Foundation of China ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) ; National Natural Science Foundation of China ; Key Research and Development Program of Guangzhou
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000682162500001
出版者	MDPI
七大方向——子方向分类	人工智能+交通
引用统计	被引频次：14[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/173211/45656
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Wang, Xiao
作者单位	1.Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Qingdao Acad Intelligent Ind, Qingdao 266000, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100091, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Tian, Yonglin,Wang, Xiao,Shen, Yu,et al. Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration[J]. REMOTE SENSING,2021,13(15):17.
APA	Tian, Yonglin,Wang, Xiao,Shen, Yu,Guo, Zhongzheng,Wang, Zilei,&Wang, Fei-Yue.(2021).Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration.REMOTE SENSING,13(15),17.
MLA	Tian, Yonglin,et al."Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration".REMOTE SENSING 13.15(2021):17.