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基于虚拟深度的聚焦型显微光场相机深度测量标定
引用本文:钱天磊,周骛,马原驰,刘慧芳,蔡小舒.基于虚拟深度的聚焦型显微光场相机深度测量标定[J].上海理工大学学报,2020,42(2):131-137.
作者姓名:钱天磊  周骛  马原驰  刘慧芳  蔡小舒
作者单位:上海理工大学能源与动力工程学院,上海 200093;上海理工大学能源与动力工程学院,上海 200093;上海理工大学能源与动力工程学院,上海 200093;上海理工大学能源与动力工程学院,上海 200093;上海理工大学能源与动力工程学院,上海 200093
基金项目:国家自然科学基金资助项目(51576130,51327803);上海市教委晨光计划(14CG46)
摘    要:针对聚焦型显微光场相机在内部光学参数未知的情况下,进行了基于虚拟深度的深度测量标定。首先基于高斯光学建立光场成像模型,推导出虚拟深度与实际深度间的函数关系。然后选择单一角点的标定板,在不同深度位置进行拍摄;该角点在多个宏像素中重复成像,相邻重复像点的间距随深度位置改变而变化;利用图像匹配的方法计算相邻重复像点的距离和虚拟深度值,并与实际深度一一对应进行曲线拟合。根据拟合结果,分析了不同深度位置下,该光场成像系统的深度测量分辨率。最后,通过拍摄已知倾角的倾斜棋盘格标定板,进行深度测量并分析测量误差,在主镜头工作距离靠近镜头方向2 mm(10倍景深)范围内,测量误差小于5.35%。

关 键 词:相机标定  聚焦型显微光场相机  深度测量  多目立体视觉  图像匹配
收稿时间:2019/2/18 0:00:00

Calibration for depth estimation by a focused micro light-field camera based on virtual depth
QIAN Tianlei,ZHOU Wu,MA Yuanchi,LIU Huifang,CAI Xiaoshu.Calibration for depth estimation by a focused micro light-field camera based on virtual depth[J].Journal of University of Shanghai For Science and Technology,2020,42(2):131-137.
Authors:QIAN Tianlei  ZHOU Wu  MA Yuanchi  LIU Huifang  CAI Xiaoshu
Institution:School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:Without knowing the intrinsic light-field parameters, a calibration process was conducted for depth estimation by a focused micro light-field camera based on virtual depth. In order to derive the functional relation between virtual depth and real depth, a light-field imaging model was established according to the Gaussian optics. A single corner calibration board was imaged at various depth distances. The corner point was multi-imaged in several macro-pixels, and the distance between adjacent redundant image points varied according to the depth value. By using an image matching algorithm, the distance between adjacent redundant image points as well as the virtual depth was calculated. After that, the curve for the relation between the virtual depth and corresponding real depth was fitted. Based on this fitted function, the resolution of depth estimation at different depths was analyzed. By capturing a slanted chessboard target, the depth estimation error was obtained. When the working distance toward the lens is within the range of 2 mm (10 times DOF), the error of depth estimation is lower than 5.35%.
Keywords:camera calibration  focused micro light-field camera  depth estimation  multi-view stereo vision  image matching
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