Blur aware calibration of multi-focus plenoptic camera

Abstract

This paper presents a novel calibration algorithm for Multi-Focus Plenoptic Cameras (MFPCs) using raw images only. The design of such cameras is usually complex and relies on precise placement of optic elements. Several calibration procedures have been proposed to retrieve the camera parameters but relying on simplified models, reconstructed images to extract features, or multiple calibrations when several types of micro-lens are used. Considering blur information, we propose a new Blur Aware Plenoptic (BAP) feature. It is first exploited in a pre-calibration step that retrieves initial camera parameters, and secondly to express a new cost function for our single optimization process. The effectiveness of our calibration method is validated by quantitative and qualitative experiments.

Source code and Datasets

The code source associated to this publication has been made open source and is publicly available here, for reproducibility and broad accessibility.

All datasets acquired or used for this publication can be accessed and downloaded here!

Citation

@inproceedings{Labussiere2020calib,
	title 	= {Blur aware calibration of multi-focus plenoptic camera},
	author 	= {Labussiere, Mathieu and Teuliere, Celine and Bernardin, Frederic and Ait-Aider, Omar},
	booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
	year 	= {2020},
	doi 	= {10.1109/CVPR42600.2020.00262},
	eprint 	= {2004.07745},
	isbn 	= {978-1-7281-7168-5},
	issn 	= {10636919},
	month 	= {jun},
	pages 	= {2542--2551},
	publisher = {IEEE},
	url 	= {https://ieeexplore.ieee.org/document/9157117/}
}