Abstract: A method for determining registration accuracy of an augmented reality system is provided. The method includes the steps of providing an input device for inputting a position of a user's touch; registering the input device with a workspace coordinate system of the augmented reality system; displaying a virtual object in a known position; recording a user's touch position in response to the user attempting to touch the virtual object; and calculating a registration error of the augmented reality system by comparing the user's touch position to the known position of the virtual object. The input device may be a passive device used in conjunction with a tracking system of the augmented reality system or an active device, such as a touch-sensitive device, coupled to the augmented reality system which outputs the user's touch position.

Abstract: A system and method for calibrating a stereo optical see-through HMD (head-mounted display). A preferred method integrates measurement for an optical see-through HMD and a six degrees of freedom tracker that is fixedly attached to the HMD to perform calibration. Calibration is based on the alignment of a stereoscopically fused marker image, which is perceived in depth, with a single 3D reference point in a world coordinate system from various viewpoints. The user interaction to perform the calibration is extremely easy compared to conventional methods and does not require keeping the head static during the calibration process.

Abstract: A method for determining registration accuracy of an augmented reality system is provided. The method includes the steps of providing an input device for inputting a position of a user's touch; registering the input device with a workspace coordinate system of the augmented reality system; displaying a virtual object in a known position; recording a user's touch position in response to the user attempting to touch the virtual object; and calculating a registration error of the augmented reality system by comparing the user's touch position to the known position of the virtual object. The input device may be a passive device used in conjunction with a tracking system of the augmented reality system or an active device, such as a touch-sensitive device, coupled to the augmented reality system which outputs the user's touch position.

Abstract: A system and method for calibrating a stereo optical see-through HMD (head-mounted display). A preferred method integrates measurement for an optical see-through HMD and a six degrees of freedom tracker that is fixedly attached to the HMD to perform calibration. Calibration is based on the alignment of a stereoscopically fused marker image, which is perceived in depth, with a single 3D reference point in a world coordinate system from various viewpoints. The user interaction to perform the calibration is extremely easy compared to conventional methods and does not require keeping the head static during the calibration process.

Abstract: A system and method for calibrating a monocular optical see-through HMD (head-mounted display). A preferred method integrates measurement for an optical see-through HMD and a six degrees of freedom tracker that is fixedly attached to the HMD to perform calibration. Calibration is based on the alignment of image points with a single 3D reference point in a world coordinate system from various viewpoints. The user interaction to perform the calibration is extremely easy compared to conventional methods and does not require keeping the head static during the calibration process. In one aspect, a calibration method comprises the steps of: displaying a marker image on one display of an HMD for view by a user; aligning the displayed marker image with a preselected reference point; collecting calibration data associated with the alignment; and computing a model of the HMD using the collected calibration data.

Abstract: The method uses a three-dimensional face model and a technique called eigenface decomposition to analyze the video at one end. The facial feature locations and eigenface coding of the face image are sent to a decoder. The decoder synthesizes the face image at the receiving end. Eigenface decoding is used to texture map a three-dimensional model warped by detected feature locations.