Abstract: Systems and methods are disclosed to enable performance of a lens distance test in head-mounted displays (HMDs) to determine the distance between a user's eye and a lens of the HMD (e.g. the display lens in a virtual or augmented reality device). In embodiments, the HMD is configured to determine a current pose of the eye based on a series of captured eye images. The pose information is used to determine the distance from the apex of the cornea to a closest point on the lens. If the determined distance is too small or too large, an alert or notification is generated instructing to adjust the HMD or change the light seal to achieve better distancing, in order to reduce the risk of eye injury and/or improve user experience. In embodiments, the lens distance test may be repeated during a user session to reevaluate and/or monitor the lens distance.

Abstract: A system for detecting a proximate object includes one or more cameras and one or more illuminators. The proximate object is detected by obtaining image data captured by the one or more cameras, where the image data is captured when at least one of the one or more illuminators are illuminated, determining brightness statistics from the image data, and determining whether the brightness statistics satisfies a predetermined threshold. The proximate object is determined to be detected in accordance with a determination that the brightness statistics satisfies the predetermined threshold.

Abstract: A computer-implemented method executed by at least one processor for reducing radial distortion errors in fish-eye images is presented. The method includes capturing an image from a camera including distortions, detecting arc-shaped edge segments in the image including the distortions, estimating a main distortion parameter by fixing a distortion centerpoint in a middle of the image, estimating the distortion centerpoint with the main distortion parameter, and obtaining an undistorted version of the captured image by inverting the distortion model.

Abstract: A computer-implemented method executed by at least one processor for reducing radial distortion errors in fish-eye images is presented. The method includes capturing an image from a camera including distortions, detecting arc-shaped edge segments in the image including the distortions, estimating a main distortion parameter by fixing a distortion centerpoint in a middle of the image, estimating the distortion centerpoint with the main distortion parameter, and obtaining an undistorted version of the captured image by inverting the distortion model.