Direct Spherical Calibration of Omnidirectional Far Infrared Camera System

Abstract

We investigate the calibration of omnidirectional (O-D) infrared (IR) camera for intelligent perception applications. Current O-D camera approaches are primarily focused on O-D color vision applications. The low-resolution O-D IR image edge boundaries are not as sharp as with color vision cameras, and as a result, the standard calibration methods were harder to use and less accurate with the low definition of the O-D IR camera. In order to more fully address O-D IR camera calibration, we propose a new calibration grid center which coordinates control point discovery methodology and a direct spherical calibration (DSC) approach for a more robust and accurate method of calibration. DSC will address the limitations of the existing methods by using the spherical coordinates of the centroid of the calibration board to directly triangulate the location of the camera center and iteratively solve the camera parameters. We compare DSC to three baseline visual calibration methodologies and augment them with additional output of the spherical results for comparison. We also look at the optimum number of calibration boards using an evolutionary algorithm and Pareto optimization to find the best method and combination of accuracy, methodology, and number of calibration boards. The benefits of DSC are both a more efficient calibration board geometry selection approach, and better accuracy than the three baseline visual calibration methodologies.