An automated calibration method for non-see-through head mounted displays

Accurate calibration of a head mounted display (HMD) is essential both for research on the visual system and for realistic interaction with virtual objects. Yet, existing calibration methods are time consuming and depend on human judgements, making them error prone, and are often limited to optical see-through HMDs. Building on our existing approach to HMD calibration Gilson et al. (2008), we show here how it is possible to calibrate a non-see-through HMD. A camera is placed inside a HMD displaying an image of a regular grid, which is captured by the camera. The HMD is then removed and the camera, which remains fixed in position, is used to capture images of a tracked calibration object in multiple positions. The centroids of the markers on the calibration object are recovered and their locations re-expressed in relation to the HMD grid. This allows established camera calibration techniques to be used to recover estimates of the HMD display's intrinsic parameters (width, height, focal length) and extrinsic parameters (optic centre and orientation of the principal ray). We calibrated a HMD in this manner and report the magnitude of the errors between real image features and reprojected features. Our calibration method produces low reprojection errors without the need for error-prone human judgements.

► Correctly calibrating a head-mounted display (HMD) is critical for the kinds of virtual reality applications used by visual neuroscientists. ► We propose a method that produces these calibrations accurately and quickly. ► Unlike methods proposed by others, ours requires no error-prone human judgements. ► Our method permits the collection of large numbers of samples for the calibration data. We show how number of samples affects calibration accuracy. ► Can be used for the more popular non-see-through HMDs, which, traditionally, have been neglected. Existing calibration techniques work only with optical-see-through HMDs.