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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 Plenop-tic (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.
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Contributor : Céline Teulière <>
Submitted on : Wednesday, April 8, 2020 - 4:15:53 PM
Last modification on : Wednesday, February 24, 2021 - 4:16:03 PM


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  • HAL Id : hal-02537124, version 1


Mathieu Labussière, Céline Teulière, Frédéric Bernardin, Omar Ait-Aider. Blur Aware Calibration of Multi-Focus Plenoptic Camera. IEEE Conference on Computer Vision and Pattern Recognition, Jun 2020, Seattle, United States. ⟨hal-02537124⟩



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