Light field imaging for computer vision: a survey

Chen JIA , Fan SHI , Meng ZHAO , Shengyong CHEN

Front. Inform. Technol. Electron. Eng ›› 2022, Vol. 23 ›› Issue (7) : 1077 -1097.

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Front. Inform. Technol. Electron. Eng ›› 2022, Vol. 23 ›› Issue (7) : 1077 -1097. DOI: 10.1631/FITEE.2100180
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Light field imaging for computer vision: a survey

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Abstract

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.

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Light field imaging / Camera array / Microlens array / Epipolar plane image / Computer vision

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Chen JIA, Fan SHI, Meng ZHAO, Shengyong CHEN. Light field imaging for computer vision: a survey. Front. Inform. Technol. Electron. Eng, 2022, 23(7): 1077-1097 DOI:10.1631/FITEE.2100180

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