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用于计算积分成像和三维重建的通用相机模型及其校准

Generic camera model and its calibration for computational integral imaging and 3D reconstruction.

作者信息

Li Weiming, Li Youfu

机构信息

Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong.

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2011 Mar 1;28(3):318-26. doi: 10.1364/JOSAA.28.000318.

Abstract

Integral imaging (II) is an important 3D imaging technology. To reconstruct 3D information of the viewed objects, modeling and calibrating the optical pickup process of II are necessary. This work focuses on the modeling and calibration of an II system consisting of a lenslet array, an imaging lens, and a charge-coupled device camera. Most existing work on such systems assumes a pinhole array model (PAM). In this work, we explore a generic camera model that accommodates more generality. This model is an empirical model based on measurements, and we constructed a setup for its calibration. Experimental results show a significant difference between the generic camera model and the PAM. Images of planar patterns and 3D objects were computationally reconstructed with the generic camera model. Compared with the images reconstructed using the PAM, the images present higher fidelity and preserve more high spatial frequency components. To the best of our knowledge, this is the first attempt in applying a generic camera model to an II system.

摘要

积分成像(II)是一种重要的三维成像技术。为了重建被观察物体的三维信息,对积分成像的光学采集过程进行建模和校准是必要的。这项工作聚焦于由微透镜阵列、成像透镜和电荷耦合器件相机组成的积分成像系统的建模和校准。大多数关于此类系统的现有工作都假定采用针孔阵列模型(PAM)。在这项工作中,我们探索了一种更具通用性的通用相机模型。该模型是基于测量的经验模型,并且我们构建了用于其校准的装置。实验结果表明通用相机模型与针孔阵列模型之间存在显著差异。使用通用相机模型对平面图案和三维物体的图像进行了计算重建。与使用针孔阵列模型重建的图像相比,这些图像呈现出更高的保真度并保留了更多的高空间频率成分。据我们所知,这是首次尝试将通用相机模型应用于积分成像系统。

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