Creating Realistic Ground Truth Data for the Evaluation of Calibration Methods for Plenoptic and Conventional Cameras

TL;DR

This paper introduces a novel backward ray tracing method to generate realistic synthetic ground truth data for calibrating both plenoptic and conventional cameras, enabling unbiased evaluation of calibration techniques.

Contribution

It presents a new approach for creating realistic synthetic calibration data using backward ray tracing, addressing limitations of previous methods and filling a gap in plenoptic camera calibration evaluation.

Findings

Provides a method for realistic synthetic data generation

Enables unbiased evaluation of calibration methods

Applicable to both plenoptic and conventional cameras

Abstract

Camera calibration methods usually consist of capturing images of known calibration patterns and using the detected correspondences to optimize the parameters of the assumed camera model. A meaningful evaluation of these methods relies on the availability of realistic synthetic data. In previous works concerned with conventional cameras the synthetic data was mainly created by rendering perfect images with a pinhole camera and subsequently adding distortions and aberrations to the renderings and correspondences according to the assumed camera model. This method can bias the evaluation since not every camera perfectly complies with an assumed model. Furthermore, in the field of plenoptic camera calibration there is no synthetic ground truth data available at all. We address these problems by proposing a method based on backward ray tracing to create realistic ground truth data that can be used for an unbiased evaluation of calibration methods for both types of cameras.