Abstract
Micro-lens array (MLA) based light field cameras have been commercialized and had a wide range of applications in various fields in recent years. To promote these applications, especially for 3D reconstruction, it is crucial to calibrate light field cameras. Among the calibration steps, it is of great importance to detect corners in checkerboard images and establish the point-to-point correspondence between the checkerboard and its images. However, almost all existing algorithms detect corners in the sub-aperture images instead of raw images for conventional light field cameras. In this paper, a corner detection algorithm that can recognize corners in the raw images of conventional light field cameras was proposed. Firstly, template matching was used to detect the 3D lines in the image space of the main lens. Then, the locations of the corners were obtained by calculating the intersection of 3D line segments and reprojecting it to the raw image again. Experimental results have demonstrated that the algorithm can still achieve good performance in actual datasets with blurred and low resolution micro lens image.
Highlights
Light field photography technology has achieved large developments in recent years since it can capture both the spatial and angular information of light rays at the same time
2) We propose a corner detection algorithm that is suitable for raw images of conventional light field cameras
The sum of NCCs of the 2D line features of L∗ in all the micro lens images of the HorArea is considered as the similarity between the 3D line segment L∗ and the actual raw data, which is represented by NCC (L∗), i.e
Summary
Light field photography technology has achieved large developments in recent years since it can capture both the spatial and angular information of light rays at the same time. A corner detection algorithm is proposed aiming at checkerboard images of conventional light field cameras. Taking raw images as the input, this algorithm find the locations of the 3D corner points of the checkerboard image in the image space of main lens by calculating intersections of two 3D line segments. After projecting these 3D corner points on micro-lens images, the coordinates of 2D corner points in raw images can be acquired. 2) We propose a corner detection algorithm that is suitable for raw images of conventional light field cameras. Experimental results demonstrate that the algorithm is accurate and works well in blured actual dataset
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