A Generic Multi-Projection-Center Model and Calibration Method for Light Field Cameras

TL;DR

This paper introduces a versatile multi-projection-center model for light field cameras, enabling accurate calibration and 3D reconstruction across various camera types through a novel parameterization and calibration method.

Contribution

The paper presents a new MPC model with 6 intrinsic parameters that generalizes light field camera representation and a calibration algorithm combining closed-form and optimization techniques.

Findings

Verified the model's effectiveness on simulated data

Achieved accurate calibration on real scene data

Demonstrated improved 3D reconstruction accuracy

Abstract

Light field cameras can capture both spatial and angular information of light rays, enabling 3D reconstruction by a single exposure. The geometry of 3D reconstruction is affected by intrinsic parameters of a light field camera significantly. In the paper, we propose a multi-projection-center (MPC) model with 6 intrinsic parameters to characterize light field cameras based on traditional two-parallel-plane (TPP) representation. The MPC model can generally parameterize light field in different imaging formations, including conventional and focused light field cameras. By the constraints of 4D ray and 3D geometry, a 3D projective transformation is deduced to describe the relationship between geometric structure and the MPC coordinates. Based on the MPC model and projective transformation, we propose a calibration algorithm to verify our light field camera model. Our calibration method includes a close-form solution and a non-linear optimization by minimizing re-projection errors. Experimental results on both simulated and real scene data have verified the performance of our algorithm.