Skip to Main content Skip to Navigation
Conference papers

Light-field camera calibration from raw images

Abstract : 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.
Document type :
Conference papers
Complete list of metadata

Cited literature [20 references]  Display  Hide  Download

https://hal.uca.fr/hal-01657735
Contributor : Michel Dhome <>
Submitted on : Thursday, October 29, 2020 - 5:13:37 PM
Last modification on : Wednesday, February 24, 2021 - 4:16:03 PM
Long-term archiving on: : Saturday, January 30, 2021 - 6:33:39 PM

File

noury_dicta2017.pdf
Files produced by the author(s)

Identifiers

Citation

Charles-Antoine Noury, Céline Teulière, Michel Dhome. Light-field camera calibration from raw images. International Conference on Digital Image Computing: Techniques and Applications (DICTA’17), Nov 2017, Sydney, Australia. pp.1-8, ⟨10.1109/DICTA.2017.8227459⟩. ⟨hal-01657735⟩

Share

Metrics

Record views

256

Files downloads

150