Real-time indoor scene reconstruction with Manhattan assumption

doi:10.1007/s11042-017-5519-7

	Real-time indoor scene reconstruction with Manhattan assumption
	Zhu, Zunjie 1; Xu, Feng 2; Yan, Chenggang 1; Li, Ning 1; Gong, Bingjian 1; Zhang, Yongdong 3; Dai, Qionghai 4
	2019
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
卷号	78 期号:1 页码:713-726
摘要	This paper presents a novel end-to-end system for real-time indoor scene reconstruction, which outperforms traditional image feature point-based method and dense geometry correspondence-based method in handling indoor scenes with less texture and geometry features. In our method, we fully explore the Manhattan assumption, i.e. scenes are majorly consisted with planar surfaces with orthogonal normal directions. Given an input depth frame, we first extract dominant axes coordinates via principle component analysis which involves the orthogonal prior and reduce the influence of noise. Then we calculate the coordinates of dominant planes (such as walls, floor and ceiling) in the coordinates using mean shift. Finally, we compute the camera orientation and reconstruct the scene by proposing a fast scheme based on matching the dominant axes and planes to the previous frame. We have tested our approach on several datasets and demonstrated that it outperforms some well known existing methods in these experiments. The performance of our method is also able to meet the requirement of real-time with an unoptimized CPU implementation.
关键词	SLAM Tracking Depth sensor Real-Time AR
DOI	10.1007/s11042-017-5519-7
收录类别	SCI
语种	英语
资助项目	National Nature Science Foundation of China[61671196] ; National Nature Science Foundation of China[61327902] ; National Nature Science Foundation of China[61671268] ; National Nature Science Foundation of China[61727808] ; Zhejiang Province Nature Science Foundation of China[LR17F030006]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000457317500040
出版者	SPRINGER
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://119.78.100.204/handle/2XEOYT63/3435
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xu, Feng; Yan, Chenggang
作者单位	1.Hangzhou Dianzi Univ, Inst Informat & Control, Hangzhou, Zhejiang, Peoples R China 2.Tsinghua Univ, Sch Software, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Tsinghua Univ, Dept Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Zunjie,Xu, Feng,Yan, Chenggang,et al. Real-time indoor scene reconstruction with Manhattan assumption[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2019,78(1):713-726.
APA	Zhu, Zunjie.,Xu, Feng.,Yan, Chenggang.,Li, Ning.,Gong, Bingjian.,...&Dai, Qionghai.(2019).Real-time indoor scene reconstruction with Manhattan assumption.MULTIMEDIA TOOLS AND APPLICATIONS,78(1),713-726.
MLA	Zhu, Zunjie,et al."Real-time indoor scene reconstruction with Manhattan assumption".MULTIMEDIA TOOLS AND APPLICATIONS 78.1(2019):713-726.