Blur Aware Calibration of Multi-Focus Plenoptic Camera

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...

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Bibliographic Details
Published inProceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 2542 - 2551
Main Authors Labussiere, Mathieu, Teuliere, Celine, Bernardin, Frederic, Ait-Aider, Omar
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2020
Subjects
Apertures
Calibration
Cameras
Feature extraction
Lenses
Optimization
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Summary: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.
ISSN:1063-6919
DOI:10.1109/CVPR42600.2020.00262