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Real-time large-scale dense mapping with surfels
Fu XY(付兴银)1,2,3,4; Zhu F(朱枫)1,3,4; Wu QX(吴清潇)1,3,4; Sun YL(孙云雷)1,2,3,4; Lu RR(鲁荣荣)1,2,3,4; Yang, Ruigang5,6
作者部门光电信息技术研究室
关键词Dense Mapping Rgb-d Camera Surfel Loop Closure Embedded Deformation Graph
发表期刊Sensors (Switzerland)
ISSN1424-8220
2018
卷号18期号:5页码:1-19
收录类别SCI ; EI
EI收录号20182005198454
WOS记录号WOS:000435580300192
产权排序1
资助机构NSFC ; State Key Laboratory of Robotics
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.

语种英语
WOS类目Chemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
关键词[WOS]SLAM ; REGISTRATION
WOS研究方向Chemistry ; Electrochemistry ; Instruments & Instrumentation
资助项目NSFC[U1713216] ; State Key Laboratory of Robotics[2017-Z21]
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/21877
专题光电信息技术研究室
通讯作者Fu XY(付兴银)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China;
3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China;
4.Key Lab of Image Understanding and Computer Vision, Shenyang 110016, China;
5.Baidu Inc., Beijing 100193, China;
6.National Engineering Laboratory of Deep Learning Technology and Application, Beijing 100193, China
推荐引用方式
GB/T 7714
Fu XY,Zhu F,Wu QX,et al. Real-time large-scale dense mapping with surfels[J]. Sensors (Switzerland),2018,18(5):1-19.
APA Fu XY,Zhu F,Wu QX,Sun YL,Lu RR,&Yang, Ruigang.(2018).Real-time large-scale dense mapping with surfels.Sensors (Switzerland),18(5),1-19.
MLA Fu XY,et al."Real-time large-scale dense mapping with surfels".Sensors (Switzerland) 18.5(2018):1-19.
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