Properly calibrating an optical see-through head-mounted display (OST-HMD) and maintaining a consistent calibration over time can be a very challenging task. Automated methods need an accurate model of both the OST-HMD screen and the user's constantly changing eye-position to correctly project virtual information. While some automated methods exist, they often have restrictions, including fixed eye-cameras that cannot be adjusted for different users.To address this problem, we have developed a method that automatically determines the position of an adjustable eye-tracking camera and its unconstrained position relative to the display. Unlike methods that require a fixed pose between the HMD and eye camera, our framework allows for automatic calibration even after adjustments of the camera to a particular individual's eye and even after the HMD moves on the user's face. Using two sets of IR-LEDs rigidly attached to the camera and OST-HMD frame, we can calculate the correct projection for different eye positions in real time and changes in HMD position within several frames. To verify the accuracy of our method, we conducted two experiments with a commercial HMD by calibrating a number of different eye and camera positions. Ground truth was measured through markers on both the camera and HMD screens, and we achieve a viewing accuracy of 1.66 degrees for the eyes of 5 different experiment participants.