par Fachada, Sarah ;Bonatto, Daniele ;Losfeld, Armand ;Senoh, Takanori;Lafruit, Gauthier ;Teratani, Mehrdad
Référence MMSP 2021(6-8 October 2021: Tampere, Finland), 2021 IEEE 23nd International Workshop on Multimedia Signal Processing
Publication Publié, 2021-10-07
Référence MMSP 2021(6-8 October 2021: Tampere, Finland), 2021 IEEE 23nd International Workshop on Multimedia Signal Processing
Publication Publié, 2021-10-07
Publication dans des actes
Résumé : | We present a novel methodology to precisely calibrate the subaperture views of an array of plenoptic 2.0 cameras. Such cameras consist of a micro lens array, and the image captured through them is a lenslet image that can be converted to a dense set of pinhole views, the so-called subaperture images. This camera array provides several dense multiview images at some sparse points of 3D space. To find the relative position of those views, simply using structure-from-motion creates misalignments due to the small disparities within each set. Additionally, a traditional calibration using calibration patterns will also fail due to the complicated objectives of plenoptic 2.0 cameras and artifacts when they are converted to subaperture views. In this paper, we propose two calibration steps (a) to register the sparse central subaperture views using Structure-from-Motion which makes it robust to artifacts in the subaperture views, and (b) to register all dense multiview sets per plenoptic camera using camera’s lenses specifications, disparity and distance to the scene. These two steps are followed by a novel merging process of the former registrations, to achieve precise calibration parameters for all the subaperture views of the multi-plenoptic array. Experimental results objectively and subjectively demonstrate high accuracy of the calibration. We show a 10% smaller reprojection error than using a naive structure-from-motion approach and verify that our method is suitable for high precision view synthesis applications such as virtual reality and holography. |