Knowledge Commons of Institute of Automation，CAS
| 3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning | |
Wang, Lei1,2,3; Meng, Weiliang4,5 ; Xi, Runping1,2; Zhang, Yanning1,2; Ma, Chengcheng4,5; Lu, Ling3; Zhang, Xiaopeng4,5
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| 发表期刊 | IEEE ACCESS
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| ISSN | 2169-3536 |
| 2019 | |
| 卷号 | 7页码:55649-55658 |
| 通讯作者 | Wang, Lei(wlei598@163.com) ; Xi, Runping(xrp@163.com) ; Zhang, Yanning(ynzhangnpu@qq.com) |
| 摘要 | We present a deep learning framework for efficient large-scale 3D point cloud analysis and classification using the designed feature description matrix (FDM). As the 3D points are unordered in the large-scale scene, and no topology structure can be employed directly for classification and recognition, it is difficult to apply deep neural network directly on 3D point clouds as points cannot be arranged in a fixed order as 2D image pixels. We design a new pipeline for 3D data processing by combining the traditional features extraction method and deep learning method. Our FDM encapsulates the 3D features of the point and can be used as the input of the deep neural network for training and testing. The experiments demonstrate that our method can acquire higher classification accuracy compared with our previous work and other state-of-art works. |
| 关键词 | CNN feature description matrix geometric features point cloud |
| DOI | 10.1109/ACCESS.2019.2909742 |
| 关键词[WOS] | MULTISCALE |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | National Natural Science Foundation of China[61561003] ; National Natural Science Foundation of China[61571439] ; National Natural Science Foundation of China[61572405] ; National Natural Science Foundation of China[61761003] ; National Natural Science Foundation of China[61571046] ; Beijing Natural Science Foundation[4184102] ; Beijing Natural Science Foundation[L182059] ; National Natural Science Foundation of China[61561003] ; National Natural Science Foundation of China[61571439] ; National Natural Science Foundation of China[61572405] ; National Natural Science Foundation of China[61761003] ; National Natural Science Foundation of China[61571046] ; Beijing Natural Science Foundation[4184102] ; Beijing Natural Science Foundation[L182059] |
| 项目资助者 | National Natural Science Foundation of China ; Beijing Natural Science Foundation |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
| WOS记录号 | WOS:000467988500001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/24207 |
| 专题 | 多模态人工智能系统全国重点实验室_三维可视计算 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Wang, Lei; Xi, Runping; Zhang, Yanning |
| 作者单位 | 1.Northwestern Polytech Univ, Sch Comp Sci & Engn, Xian 710072, Shaanxi, Peoples R China 2.Natl Engn Lab Integrated Aerospace Ground Ocean B, Xian 710072, Shaanxi, Peoples R China 3.East China Univ Technol, Jiangxi Engn Lab Radioact Geosci & Big Data Techn, Nanchang 330013, Jiangxi, Peoples R China 4.CAS Inst Automat, LIAMA NLPR, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Lei,Meng, Weiliang,Xi, Runping,et al. 3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning[J]. IEEE ACCESS,2019,7:55649-55658. |
| APA | Wang, Lei.,Meng, Weiliang.,Xi, Runping.,Zhang, Yanning.,Ma, Chengcheng.,...&Zhang, Xiaopeng.(2019).3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning.IEEE ACCESS,7,55649-55658. |
| MLA | Wang, Lei,et al."3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning".IEEE ACCESS 7(2019):55649-55658. |
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| 3d point cloud analy（2719KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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