Camera calibration is an initial step employed in many computer vision applications for the estimation of camera parameters. Along with images of an arbitrary scene, these parameters allow for inference of the scene’s metric information. This is a primary reason for camera calibration’s significance to computer vision. In this paper, we present a novel approach to solving the camera calibration problem. The method was developed as part of a Human Computer Interaction (HCI) System for the NASA Virtual GloveBox (VGX) Project. Our algorithm is based on the geometric properties of perspective projections and provides a closed form solution for the camera parameters. Its accuracy is evaluated in the context of the NASA VGX, and the results indicate that our algorithm achieves accuracy similar to other calibration methods which are characterized by greater complexity and computational cost. Because of its reliability and wide variety of potential applications, we are confident that our calibration algorithm will be of interest to many.