CIOMP OpenIR
Three-dimentional reconstruction of semantic scene based on RGB-D map
Lin, Jin-Hua; Wang, Yan-Jie
2018
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
ISSN1004924X
卷号26期号:5页码:1231-1241
摘要Reconstruction of 3D object is an important part in machine vision system, and the semantic understanding of 3D object is a core function for the machine vision system. In this paper, 3D restoration was combined with the semantic understanding of 3D object, a 3D semantic scene recovery network was proposed. The semantic classification and scene restoration of 3D scene were achieved only by using a single RGB-D map as input. Firstly, an end-to-end 3D convolution neural network was established. The input of the network was a depth map. The 3D context module was used for learning the region within the camera view, then the 3D voxels with semantic labels were generated. Secondly, a synthetic data set with dense volume labels was established to train the depth learning network. Finally, the experimental results showed that the recovery performance w improved by 2.0% compared with the state-of-art. It can be seen that the 3D learning network plays well in 3D scene restoration, it owns high accuracy in semantic annotation of object in the scene. 2018, Science Press. All right reserved.
关键词Image reconstruction Computer system recovery Computer vision Convolution Learning systems Machinery Restoration Semantics Three dimensional computer graphics
DOI10.3788/OPE.20182605.1231
收录类别EI
引用统计
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/60838
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
Lin, Jin-Hua,Wang, Yan-Jie. Three-dimentional reconstruction of semantic scene based on RGB-D map[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2018,26(5):1231-1241.
APA Lin, Jin-Hua,&Wang, Yan-Jie.(2018).Three-dimentional reconstruction of semantic scene based on RGB-D map.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,26(5),1231-1241.
MLA Lin, Jin-Hua,et al."Three-dimentional reconstruction of semantic scene based on RGB-D map".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 26.5(2018):1231-1241.
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