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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.

A Corner Detection Method for Conventional Light Field Camera by Jointly Using Line-Features