Dynamic (de)focused projection for three-dimensional reconstruction

被引:8
|
作者
Lertrusdachakul, Intuon [1 ]
Fougerolle, Yohan D. [1 ]
Laligant, Olivier [1 ]
机构
[1] Le2i Lab, F-71200 Le Creusot, Burgundy, France
关键词
focus; depth from defocus; active illumination pattern; range sensors; blur estimation; 3-D reconstruction; DEPTH; DEFOCUS; FOCUS; SHAPE;
D O I
10.1117/1.3644541
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
We present a novel 3-D recovery method based on structured light. This method unifies depth from focus (DFF) and depth from defocus (DFD) techniques with the use of a dynamic (de) focused projection. With this approach, the image acquisition system is specifically constructed to keep a whole object sharp in all the captured images. Therefore, only the projected patterns experience different defocused deformations according to the object's depths. When the projected patterns are out of focus, their point-spread function (PSF) is assumed to follow a Gaussian distribution. The final depth is computed by the analysis of the relationship between the sets of PSFs obtained from different blurs and the variation of the object's depths. Our new depth estimation can be employed as a stand-alone strategy. It has no problem with occlusion and correspondence issues. Moreover, it handles textureless and partially reflective surfaces. The experimental results on real objects demonstrate the effective performance of our approach, providing reliable depth estimation and competitive time consumption. It uses fewer input images than DFF, and unlike DFD, it ensures that the PSF is locally unique. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3644541]
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Three-dimensional curve reconstruction from multiple images
    Mai, F.
    Hung, Y. S.
    IET COMPUTER VISION, 2012, 6 (04) : 273 - 284
  • [42] Three-dimensional focal stack imaging in scanning transmission X-ray microscopy with an improved reconstruction algorithm
    Ma, Limei
    Zhang, Xiangzhi
    Xu, Zijian
    Spath, Andreas
    Xing, Zhenjiang
    Sun, Tianxiao
    Tai, Renzhong
    OPTICS EXPRESS, 2019, 27 (05): : 7787 - 7802
  • [43] Optical three-dimensional metrology with structured illumination
    Tutsch, Rainer
    Petz, Marcus
    Fischer, Marc
    OPTICAL ENGINEERING, 2011, 50 (10)
  • [44] Fringe-projection method for three-dimensional digitization of human faces
    Picos, Kenia
    Juarez-Salazar, Rigoberto
    Diaz-Ramirez, Victor H.
    OPTICS AND PHOTONICS FOR INFORMATION PROCESSING X, 2016, 9970
  • [45] Three-Dimensional Spine Model Reconstruction Using One-Class SVM Regularization
    Lecron, Fabian
    Boisvert, Jonathan
    Mahmoudi, Said
    Labelle, Hubert
    Benjelloun, Mohammed
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2013, 60 (11) : 3256 - 3264
  • [46] An improved genetic algorithm for three-dimensional reconstruction from a single uniform texture image
    Sun, Yujuan
    Zhang, Xiaofeng
    Jian, Muwei
    Wang, Shengke
    Wu, Zeju
    Su, Qingtang
    Chen, Beijing
    SOFT COMPUTING, 2018, 22 (02) : 477 - 486
  • [47] Research progress in three-dimensional reconstruction of the rat spinal tract
    Wu, Huiqun
    Lu, Guangming
    NEURAL REGENERATION RESEARCH, 2008, 3 (03) : 317 - 320
  • [48] Three-dimensional reconstruction of icosahedral particles from single micrographs in real time at the microscope
    Cardone, Giovanni
    Yan, Xiaodong
    Sinkovits, Robert S.
    Tang, Jinghua
    Baker, Timothy S.
    JOURNAL OF STRUCTURAL BIOLOGY, 2013, 183 (03) : 329 - 341
  • [49] A Variational Stereo Method for the Three-Dimensional Reconstruction of Ocean Waves
    Gallego, Guillermo
    Yezzi, Anthony
    Fedele, Francesco
    Benetazzo, Alvise
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (11): : 4445 - 4457
  • [50] Three-Dimensional Reconstruction of Light Field Based on Phase Similarity
    Feng, Wei
    Gao, Junhui
    Qu, Tong
    Zhou, Shiqi
    Zhao, Daxing
    SENSORS, 2021, 21 (22)