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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2100180


Light field imaging for computer vision: a survey


Author(s):  Chen JIA, Fan SHI, Meng ZHAO, Sheng-yong CHEN

Affiliation(s):  Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), Tianjin University of Technology, Tianjin 300384, China; more

Corresponding email(s):   shifan@email.tjut.edu.cn

Key Words:  Light field imaging, Camera array, Microlens array, Epipolar plane image, Computer vision


Chen JIA, Fan SHI, Meng ZHAO, Sheng-yong CHEN. Light field imaging for computer vision: a survey[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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Abstract: 
Light field (LF) imaging has attracted attention because of its ability to solve computer vision problems. This paper briefly reviews 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 camera or microlens arrays to record the position and direction in-formation of light rays, acquiring complete three-dimensional (3D) scene information. The contribution of LF imaging im-proves the accuracy of depth estimation, image segmentation, blending, fusion and 3D reconstruction. LF has also been innovatively applied for recognizing irises and faces, identification of materials and fake pedestrians, acquisition of epipo-lar plane images and shape recovery, and LF microscopy. Here, we further summarise the existing problems and the devel-opment trends of LF imaging in computer vision, such as the establishment and evaluation of the LF dataset, application under high dynamic range (HDR) conditions, LF enhancement, and virtual reality. LF imaging has achieved great success in various studies. Over the past 25 years, more than 180 relevant publications have reported the capability of LF imaging in solving computer vision problems. We summarise these reports to make it easier for researchers to search the detailed methods for specific solutions.

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