  Camera calibration plays a critical role in various computer vision tasks
such as autonomous driving or augmented reality. Widely used camera calibration
tools utilize plane pattern based methodology, such as using a chessboard or
AprilTag board, user's calibration expertise level significantly affects
calibration accuracy and consistency when without clear instruction.
Furthermore, calibration is a recurring task that has to be performed each time
the camera is changed or moved. It's also a great burden to calibrate huge
amounts of cameras such as Driver Monitoring System (DMS) cameras in a
production line with millions of vehicles. To resolve above issues, we propose
a calibration system called Calibration with Pose Guidance to improve
calibration accuracy, reduce calibration variance among different users or
different trials of the same person. Experiment result shows that our proposed
method achieves more accurate and consistent calibration than traditional
calibration tools.
