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Deep Learning on Point Clouds and Its Application: A Survey

文献类型：期刊论文

作者Liu, Weiping2; Sun, Jia1; Li, Wanyi1; Hu, Ting2; Wang, Peng1
刊名SENSORS
出版日期2019-10-01
卷号19期号:19页码:22
关键词feature learning deep learning point cloud application of point cloud
DOI10.3390/s19194188
通讯作者Li, Wanyi(wanyi.li@ia.ac.cn) ; Hu, Ting(tinghu@whu.edu.cn)
英文摘要Point cloud is a widely used 3D data form, which can be produced by depth sensors, such as Light Detection and Ranging (LIDAR) and RGB-D cameras. Being unordered and irregular, many researchers focused on the feature engineering of the point cloud. Being able to learn complex hierarchical structures, deep learning has achieved great success with images from cameras. Recently, many researchers have adapted it into the applications of the point cloud. In this paper, the recent existing point cloud feature learning methods are classified as point-based and tree-based. The former directly takes the raw point cloud as the input for deep learning. The latter first employs a k-dimensional tree (Kd-tree) structure to represent the point cloud with a regular representation and then feeds these representations into deep learning models. Their advantages and disadvantages are analyzed. The applications related to point cloud feature learning, including 3D object classification, semantic segmentation, and 3D object detection, are introduced, and the datasets and evaluation metrics are also collected. Finally, the future research trend is predicted.
WOS关键词OBJECT RECOGNITION ; SEGMENTATION ; CLASSIFICATION
资助项目National Natural Science Foundation of China[61771471] ; National Natural Science Foundation of China[91748131] ; National Natural Science Foundation of China[U1613213] ; National Key Research and Development Plan of China[2017YFB1300202] ; China Postdoctoral Science Foundation[2018M641523] ; Youth Innovation Promotion Association Chinese Academy of Sciences (CAS)[2015112]
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
出版者MDPI
WOS记录号WOS:000494823200132
资助机构National Natural Science Foundation of China ; National Key Research and Development Plan of China ; China Postdoctoral Science Foundation ; Youth Innovation Promotion Association Chinese Academy of Sciences (CAS)
源URL[http://ir.ia.ac.cn/handle/173211/28914]  
专题智能机器人系统研究
通讯作者Li, Wanyi; Hu, Ting
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Weiping,Sun, Jia,Li, Wanyi,et al. Deep Learning on Point Clouds and Its Application: A Survey[J]. SENSORS,2019,19(19):22.
APA Liu, Weiping,Sun, Jia,Li, Wanyi,Hu, Ting,&Wang, Peng.(2019).Deep Learning on Point Clouds and Its Application: A Survey.SENSORS,19(19),22.
MLA Liu, Weiping,et al."Deep Learning on Point Clouds and Its Application: A Survey".SENSORS 19.19(2019):22.

入库方式： OAI收割

来源：自动化研究所

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