Histograms of Gaussian normal distribution for 3D feature matching in cluttered scenes | |
Zhou, Wei1,3,4; Ma, Caiwen2; Yao, Tong1,3; Chang, Peng5; Zhang, Qi3; Kuijper, Arjan4 | |
作者部门 | 光电跟踪与测量技术研究室 |
2019-04 | |
发表期刊 | VISUAL COMPUTER |
ISSN | 0178-2789;1432-2315 |
卷号 | 35期号:4页码:489-505 |
产权排序 | 1 |
摘要 | 3D feature descriptors provide essential information to find given models in captured scenes. In practical applications, these scenes often contain clutter. This imposes severe challenges on the 3D object recognition leading to feature mismatches between scenes and models. As such errors are not fully addressed by the existing methods, 3D feature matching still remains a largely unsolved problem. We therefore propose our Histograms of Gaussian Normal Distribution (HGND) for capturing salient feature information on a local reference frame (LRF) that enables us to solve this problem. We define a LRF on each local surface patch by using the eigenvectors of the scatter matrix. Different from the traditional local LRF-based methods, our HGND descriptor is based on the combination of geometrical and spatial information without calculating the distribution of every point and its geometrical information in a local domain. This makes it both simple and efficient. We encode the HGND descriptors in a histogram by the geometrical projected distribution of the normal vectors. These vectors are based on the spatial distribution of the points. We use three public benchmarks, the Bologna, the UWA and the Ca' Foscari Venezia dataset, to evaluate the speed, robustness, and descriptiveness of our approach. Our experiments demonstrate that the HGND is fast and obtains a more reliable matching rate than state-of-the-art approaches in cluttered situations. |
关键词 | Local surface patch Local reference frame Local feature descriptor Point cloud |
DOI | 10.1007/s00371-018-1478-x |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000463672800003 |
出版者 | SPRINGER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/31376 |
专题 | 光电跟踪与测量技术研究室 |
通讯作者 | Zhou, Wei |
作者单位 | 1.Xian Inst Opt & Precis Mech CAS, Xian 710119, Shaanxi, Peoples R China 2.Xian Inst Opt & Precis Mech CAS, Signal & Informat Proc, Xian 710119, Shaanxi, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Tech Univ Darmstadt, Fraunhofer IGD, D-64283 Darmstadt, Germany 5.Northeastern Univ, Elect & Comp Engn, Boston, MA 02115 USA |
推荐引用方式 GB/T 7714 | Zhou, Wei,Ma, Caiwen,Yao, Tong,et al. Histograms of Gaussian normal distribution for 3D feature matching in cluttered scenes[J]. VISUAL COMPUTER,2019,35(4):489-505. |
APA | Zhou, Wei,Ma, Caiwen,Yao, Tong,Chang, Peng,Zhang, Qi,&Kuijper, Arjan.(2019).Histograms of Gaussian normal distribution for 3D feature matching in cluttered scenes.VISUAL COMPUTER,35(4),489-505. |
MLA | Zhou, Wei,et al."Histograms of Gaussian normal distribution for 3D feature matching in cluttered scenes".VISUAL COMPUTER 35.4(2019):489-505. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Histograms of Gaussi(3114KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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