Real-time large-scale dense mapping with surfels
文献类型：期刊论文
| 作者 | Yang, Ruigang; Lu RR(鲁荣荣); Sun YL(孙云雷); Fu XY(付兴银); Zhu F(朱枫); Wu QX(吴清潇); Song HL(宋海龙) ; Liu Z(刘哲)
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| 刊名 | Sensors (Switzerland)
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| 出版日期 | 2018 |
| 卷号 | 18期号:5页码:1-19 |
| 关键词 | dense mapping RGB-D camera surfel loop closure embedded deformation graph |
| ISSN号 | 1424-8220 |
| 产权排序 | 1 |
| 通讯作者 | Fu XY(付兴银) |
| 中文摘要 | Real-time dense mapping systems have been developed since the birth of consumer RGB-D cameras. Currently, there are two commonly used models in dense mapping systems: truncated signed distance function (TSDF) and surfel. The state-of-the-art dense mapping systems usually work fine with small-sized regions. The generated dense surface may be unsatisfactory around the loop closures when the system tracking drift grows large. In addition, the efficiency of the system with surfel model slows down when the number of the model points in the map becomes large. In this paper, we propose to use two maps in the dense mapping system. The RGB-D images are integrated into a local surfel map. The old surfels that reconstructed in former times and far away from the camera frustum are moved from the local map to the global map. The updated surfels in the local map when every frame arrives are kept bounded. Therefore, in our system, the scene that can be reconstructed is very large, and the frame rate of our system remains high. We detect loop closures and optimize the pose graph to distribute system tracking drift. The positions and normals of the surfels in the map are also corrected using an embedded deformation graph so that they are consistent with the updated poses. In order to deal with large surface deformations, we propose a new method for constructing constraints with system trajectories and loop closure keyframes. The proposed new method stabilizes large-scale surface deformation. Experimental results show that our novel system behaves better than the prior state-of-the-art dense mapping systems. |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000435580300192 |
| 源URL | [http://ir.sia.cn/handle/173321/21854]  |
| 专题 | 沈阳自动化研究所_装备制造技术研究室 沈阳自动化研究所_其他 |
| 作者单位 | 1.Key Lab of Image Understanding and Computer Vision, Shenyang 110016, China 2.National Engineering Laboratory of Deep Learning Technology and Application, Beijing 100193, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.University of Chinese Academy of Sciences, Beijing 100049, China 5.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China 6.Baidu Inc., Beijing 100193, China |
| 推荐引用方式 GB/T 7714 | Yang, Ruigang,Lu RR,Sun YL,et al. Real-time large-scale dense mapping with surfels[J]. Sensors (Switzerland),2018,18(5):1-19. |
| APA | Yang, Ruigang.,Lu RR.,Sun YL.,Fu XY.,Zhu F.,...&刘哲.(2018).Real-time large-scale dense mapping with surfels.Sensors (Switzerland),18(5),1-19. |
| MLA | Yang, Ruigang,et al."Real-time large-scale dense mapping with surfels".Sensors (Switzerland) 18.5(2018):1-19. |
入库方式： OAI收割
来源：沈阳自动化研究所
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