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High quality depth map estimation of object surface from light-field images
Liu, Fei1,2; Hou, Guangqi2; Sun, Zhenan2; Tan, Tieniu2; Guangqi Hou
2017-08-23
发表期刊NEUROCOMPUTING
卷号252期号:252页码:3-16
文章类型Article
摘要
; Light-field imaging provides a novel solution to the passive 3D imaging technology. However the dense multi-view sub-aperture images decoded from the light-field raw image have extremely narrow baselines, which lead to inconsistent matching with terrible blurriness and ambiguities. This paper presents an accurate depth estimation algorithm for object surface using a lenslet light-field camera. The input data for depth estimation can be both light-field videos and images under indoor and outdoor environment. To tackle the continuously changing outdoor illumination and take full advantage of rays, rendering enhancement is performed through denoising and local vignetting correction for obtaining high-fidelity 4D light fields. The novel sub-aperture image pair selection and stereo matching algorithm are proposed for disparity computation. Then we apply the disparity refinement for recovering high quality surface details and handling disparity discontinuities. Finally both commercial and self-developed light-field cameras are used to capture real-world scenes with various lighting conditions and poses. The accuracy and robustness of the proposed algorithm are evaluated both on synthetic light-field datasets and real-world scenes by comparing with state-of-the-art algorithms. The experimental results show that high quality depth maps are recovered with smooth surfaces and accurate geometry structures. (C) 2017 Elsevier B.V. All rights reserved.
关键词Light Field Depth Estimation Stereo Matching Disparity Refinement
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2016.09.136
关键词[WOS]BELIEF PROPAGATION ; STEREO
收录类别SCI
语种英语
项目资助者National Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61420106015 ; 61302184 ; 61273272)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000405884500002
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/19632
专题智能感知与计算研究中心
通讯作者Guangqi Hou
作者单位1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing, Peoples R China
2.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit,Inst Automat, Beijing, Peoples R China
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GB/T 7714
Liu, Fei,Hou, Guangqi,Sun, Zhenan,et al. High quality depth map estimation of object surface from light-field images[J]. NEUROCOMPUTING,2017,252(252):3-16.
APA Liu, Fei,Hou, Guangqi,Sun, Zhenan,Tan, Tieniu,&Guangqi Hou.(2017).High quality depth map estimation of object surface from light-field images.NEUROCOMPUTING,252(252),3-16.
MLA Liu, Fei,et al."High quality depth map estimation of object surface from light-field images".NEUROCOMPUTING 252.252(2017):3-16.
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