Light-Field Camera Calibration from Raw Images

• Published in: 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA) pp. 1 - 8
• Main Authors: Noury, Charles-Antoine, Teuliere, Celine, Dhome, Michel
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2017
• Subjects: Calibration; Cameras; Distortion; Feature extraction; Lenses; Optical distortion; Three-dimensional displays
• DOI: 10.1109/DICTA.2017.8227459

This paper presents a new calibration method for lenslet-based plenoptic cameras. While most existing approaches require the computation of sub-aperture images or depth maps which quality depends on some calibration parameters, the proposed process uses the raw image directly. We detect micro-images containing checkerboard corners and use a pattern registration method to estimate their positions with subpixelic accuracy. We present a more complete geometrical model than previous work composed of 16 intrinsic parameters. This model relates 3D points to their corresponding image projections. We introduce a new cost function based on reprojection errors of both checkerboard corners and micro-lenses centers in the raw image space. After the initialization process, all intrinsic and extrinsic parameters are refined with a non-linear optimization. The proposed method is validated in simulation as well as on real images.