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.
摘要
光场成像因其解决计算机视觉问题的能力而备受关注。本文首先简要回顾了近年来计算机视觉的研究进展。对于影响计算机视觉发展的大多数因素来说, 视觉信息获取的丰富性和准确性起着决定性作用。光场成像技术利用照相机或微透镜阵列记录光线位置和方向信息, 获取完整三维场景信息, 为计算机视觉研究做出巨大贡献。光场成像提高了深度估计以及图像分割、融合和三维重建的精度。光场成像还被创新地应用于虹膜和人脸识别、材料和虚假行人识别、极平面图像采集和形状恢复以及光场显微镜。我们进一步总结了光场成像技术在计算机视觉研究中存在的问题和发展趋势, 如光场数据集的建立和评估、在高动态范围条件下的应用、光场增强和虚拟现实。光场成像在各种研究中取得巨大成功。在过去25年, 超过180篇文献报道了光场成像在解决计算机视觉问题上的能力。我们梳理了这些文献, 使研究人员更容易搜索有关解决方案的详细方法。
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Project supported by the National Natural Science Foundation of China (Nos. 61906133, 62020106004, and 92048301)
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Chen JIA and Fan SHI investigated and summarized the literature. Chen JIA and Meng ZHAO drafted the paper. Chen JIA and Shengyong CHEN revised and finalized the paper.
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Chen JIA, Fan SHI, Meng ZHAO, and Shengyong CHEN declare that they have no conflict of interest.
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Jia, C., Shi, F., Zhao, M. et al. Light field imaging for computer vision: a survey. Front Inform Technol Electron Eng 23, 1077–1097 (2022). https://doi.org/10.1631/FITEE.2100180
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DOI: https://doi.org/10.1631/FITEE.2100180