| 论文标题 |
A multi-frame graph matching algorithm for low-bandwidth RGB-D SLAM |
| 作者列表 |
Shuai Zheng, Jun Hong, Kang Zhang, Baotong Li, Xin Li |
| 第一作者 |
Shuai Zheng |
| 类别 |
期刊文章 |
| 期刊名称 |
computer-aided design |
| 会议名称 |
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| 卷号、期、页码 |
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| 年度 |
2016 |
| 地点 |
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| SCI检索号 |
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| EI检索号 |
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| 隶属方向 |
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| 简介 |
This paper presents a novel multi-frame graph matching algorithm for reliable partial alignments among point clouds. We use this algorithm to stitch frames for 3D environment reconstruction. The idea is to
utilize both descriptor similarity and mutual spatial coherency of features existed in multiple frames to match these frames. The proposed multi-frame matching algorithm can extract coarse correspondence
among multiple point clouds more reliably than pairwise matching algorithms, especially when the data are noisy and the overlap is relatively small. When there are insufficient consistent features that appeared
in all these frames, our algorithm reduces the number of frames to match to deal with it adaptively. Hence, it is particularly suitable for cost-efficient robotic Simultaneous Localization and Mapping (SLAM).
We design a prototype system integrating our matching and reconstruction algorithm on a remotely controlled navigation iRobot, equipped with a Kinect and a Raspberry Pi. Our reconstruction experiments demonstrate the effectiveness of our algorithm and design.
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| 参考条目 |
Zheng S, et al. A multi-frame graph matching algorithm for low-bandwidth RGB-D SLAM Computer-Aided Design (2016)
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| 提交日期 |
2016-06-15 |