Light-Field Camera Calibration from Raw Images

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...

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Bibliographic Details
Published in2017 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
LanguageEnglish
Published IEEE 01.11.2017
Subjects
Calibration
Cameras
Distortion
Feature extraction
Lenses
Optical distortion
Three-dimensional displays
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Summary: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.
DOI:10.1109/DICTA.2017.8227459