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3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection | |
Mengqi Rong1,2![]() ![]() | |
发表期刊 | IEEE Transactions on Circuits and Systems for Video Technology
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ISSN | 1051-8215 |
2023-05-05 | |
卷号 | 33期号:12页码:early-access |
通讯作者 | Shen, Shuhan(shshen@nlpr.ia.ac.cn) |
文章类型 | 期刊论文 |
摘要 | Semantic segmentation of 3D scenes is one of the most important tasks in the field of computer vision and has attracted much attention. In this paper, we propose a novel framework for 3D semantic segmentation of aerial photogrammetry models, which uses orthographic projection to improve efficiency while still ensuring high precision, and can also be applied to multiple types of models (i.e., textured mesh or colored point cloud). In our pipeline, we first obtain RGB images and elevation images from the 3D scene through orthographic projection, then use the image semantic segmentation network to segment these images to obtain pixel-wise semantic predictions, and finally back-project the segmentation results to the 3D model for fusion. Specifically, for the image semantic segmentation model, we design a cross-modality feature aggregation module and a context guidance module based on category features, which assist the network in learning more discriminative features between different objects. For the 2D-3D semantic fusion, we combine the segmentation results of the 2D images with the geometric consistency of the 3D models for joint optimization, which further improves the accuracy of the 3D semantic segmentation. Extensive experiments on two large-scale urban scenes demonstrate the efficiency and feasibility of our algorithm and surpass the current mainstream 3D deep learning methods. |
关键词 | 3D scenes semantic segmentation orthographic projection |
DOI | 10.1109/TCSVT.2023.3273224 |
关键词[WOS] | NETWORK |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:001121618300034 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 三维视觉 |
国重实验室规划方向分类 | 环境多维感知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52436 |
专题 | 中国科学院工业视觉智能装备工程实验室_精密感知与控制 |
通讯作者 | Shuhan Shen |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 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 | Mengqi Rong,Shuhan Shen. 3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection[J]. IEEE Transactions on Circuits and Systems for Video Technology,2023,33(12):early-access. |
APA | Mengqi Rong,&Shuhan Shen.(2023).3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection.IEEE Transactions on Circuits and Systems for Video Technology,33(12),early-access. |
MLA | Mengqi Rong,et al."3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection".IEEE Transactions on Circuits and Systems for Video Technology 33.12(2023):early-access. |
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