Optimization of estimating intrinsic parameters of a camera using a robot arm

Abstract

Eye-tracking technology is applied across industries such as automotive, aerospace, and human-computer interaction, where precise gaze estimation relies on the accurate calibration of eye-tracking cameras. In this work, a robot arm is used to perform the intrinsic calibration of eye tracking cameras. The motivation behind using a robotic arm for the intrinsic calibration of an eye-tracking camera instead of a manual procedure stems from several key advantages related to precision, repeatability, and efficiency. Control over the camera poses in front of the checkerboard leads to a more accurate and efficient calibration process. This eliminates the challenges and inconsistencies associated with manual camera movements and opens the door for automating and scaling the calibration process with minimal human involvement. The robotic arm ensures a level of consistency and reliability that would be hard to achieve manually, making it a compelling choice for eye-tracking camera calibration, especially in high-precision applications.