Corner-Based Geometric Calibration of Multi-focus Plenoptic Cameras

Sotiris Nousias, F. Chadebecq, Jonas Pichat, P. Keane, S. Ourselin, C. Bergeles
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引用次数: 22

Abstract

We propose a method for geometric calibration of multifocus plenoptic cameras using raw images. Multi-focus plenoptic cameras feature several types of micro-lenses spatially aligned in front of the camera sensor to generate micro-images at different magnifications. This multi-lens arrangement provides computational-photography benefits but complicates calibration. Our methodology achieves the detection of the type of micro-lenses, the retrieval of their spatial arrangement, and the estimation of intrinsic and extrinsic camera parameters therefore fully characterising this specialised camera class. Motivated from classic pinhole camera calibration, our algorithm operates on a checker-board’s corners, retrieved by a custom microimage corner detector. This approach enables the introduction of a reprojection error that is used in a minimisation framework. Our algorithm compares favourably to the state-of-the-art, as demonstrated by controlled and freehand experiments, making it a first step towards accurate 3D reconstruction and Structure-from-Motion.
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基于角点的多焦全光相机几何定标
提出了一种基于原始图像的多焦全光相机几何定标方法。多焦全光学相机的特点是在相机传感器前空间排列几种微镜头,以产生不同放大倍数的微图像。这种多镜头排列提供了计算摄影的好处,但使校准复杂化。我们的方法实现了微透镜类型的检测,它们的空间排列的检索,以及内在和外在相机参数的估计,因此充分表征了这种专业相机类。受经典针孔相机校准的启发,我们的算法在棋盘的角上运行,由自定义的微图像角检测器检索。这种方法可以引入在最小化框架中使用的重投影误差。我们的算法与最先进的算法相比,如控制和徒手实验所示,使其成为迈向精确3D重建和运动结构的第一步。
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