Light field imaging for computer vision: a survey

被引:9
作者
JIA, Chen [1 ,2 ]
SHI, Fan [1 ,2 ]
ZHAO, Meng [1 ,2 ]
CHEN, Shengyong [1 ,2 ]
机构
[1] Tianjin Univ Technol, Minist Educ, Engn Res Ctr Learning Based Intelligent Syst, Tianjin 300384, Peoples R China
[2] Tianjin Univ Technol, Key Lab Comp Vis & Syst, Minist Educ, Tianjin 300384, Peoples R China
基金
中国国家自然科学基金;
关键词
Light field imaging; Camera array; Microlens array; Epipolar plane image; Computer vision; TP391; 4; QUALITY ASSESSMENT; MICROSCOPE; SEGMENTATION; PERFORMANCE; SALIENCY; FACE;
D O I
10.1631/FITEE.2100180
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Light field (LF) imaging has attracted attention because of its ability to solve computer vision problems. In this paper we briefly review the research progress in computer vision in recent years. For most factors that affect computer vision development, the richness and accuracy of visual information acquisition are decisive. LF imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays, acquiring complete three-dimensional (3D) scene information. LF imaging technology improves the accuracy of depth estimation, image segmentation, blending, fusion, and 3D reconstruction. LF has also been innovatively applied to iris and face recognition, identification of materials and fake pedestrians, acquisition of epipolar plane images, shape recovery, and LF microscopy. Here, we further summarize the existing problems and the development trends of LF imaging in computer vision, including the establishment and evaluation of the LF dataset, applications under high dynamic range (HDR) conditions, LF image enhancement, virtual reality, 3D display, and 3D movies, military optical camouflage technology, image recognition at micro-scale, image processing method based on HDR, and the optimal relationship between spatial resolution and four-dimensional (4D) LF information acquisition. LF imaging has achieved great success in various studies. Over the past 25 years, more than 180 publications have reported the capability of LF imaging in solving computer vision problems. We summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.
引用
收藏
页码:1077 / 1097
页数:21
相关论文
共 100 条
[1]  
Adelson E.H., 1991, Computational Models of Visual Processing, P3
[2]   REAL-TIME FPGA IMPLEMENTATION OF LINEAR BLENDING VISION RECONSTRUCTION ALGORITHM USING A SPHERICAL LIGHT FIELD CAMERA [J].
Afshari, Hossein ;
Akin, Abdulkadir ;
Popovic, Vladan ;
Schmid, Alexandre ;
Leblebici, Yusuf .
2012 IEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS (SIPS), 2012, :49-54
[3]   A Variational Model for Intrinsic Light Field Decomposition [J].
Alperovich, Anna ;
Goldluecke, Bastian .
COMPUTER VISION - ACCV 2016, PT III, 2017, 10113 :66-82
[4]  
[Anonymous], 2016, 8 INT C QUAL MULT EX
[5]  
[Anonymous], 2013, P 8 CHIN C BIOM REC, DOI DOI 10.1007/978-3-319-02961-0_43
[6]  
[Anonymous], 2016, PROC C VISION MODELI, DOI DOI 10.5555/3056901.3056924
[7]   Real-time 3D light field transmission [J].
Balogh, Tibor ;
Kovacs, Peter Tamas .
REAL-TIME IMAGE AND VIDEO PROCESSING 2010, 2010, 7724
[8]   Segmentation of epipolar-plane image volumes with occlusion and disocclusion competition [J].
Berent, Jesse ;
Dragotti, Pier Luigi .
2006 IEEE WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, 2006, :182-+
[9]   Wave optics theory and 3-D deconvolution for the light field microscope [J].
Broxton, Michael ;
Grosenick, Logan ;
Yang, Samuel ;
Cohen, Noy ;
Andalman, Aaron ;
Deisseroth, Karl ;
Levoy, Marc .
OPTICS EXPRESS, 2013, 21 (21) :25418-25439
[10]  
Campbell N. D. F., 2011, 2011 Conference for Visual Media Production, P126, DOI 10.1109/CVMP.2011.21