Nuno Barroso Monteiro

First prototypes of standard plenoptic cameras (SPCs) were based on arrays of pinhole cameras. Despite the array nature, viewpoint pinhole arrays are not intrinsically provided by current SPC calibration tools. In this work, we start by detailing the mapping between the SPC model and a camera array of viewpoints. Then, the mapping is used to propose a calibration procedure for the SPC based on a grid of corners. Calibration involves two steps, first a linear solution and then a nonlinear optimization minimizing the ray re-projection error. The proposed calibration methodology compares favourably with state of the art calibrations and the linear solution proposed for the initial stage of the calibration outperforms the state of the art.

Plenoptic cameras allow to recover the structure of a scene from a single image. Recent works on scene structure estimation recover the disparity associated with each pixel but do not consider metric depth. In this work, we propose a methodology for scene metric reconstruction that estimates initial disparity values by analyzing the epipolar plane images. A dense estimate of disparities is obtained by regularization. These disparity estimates are then converted to 3D metric information using the intrinsic parameters of the plenoptic camera. Experiments have been conducted both with simulated and real cameras yielding promising results.