Abstract: Techniques of tracking a user's gaze includes identifying a region of a display at which a gaze of a user is directed, the region including a plurality of pixels. By determining a region rather than a point, when the regions correspond to elements of a user interface, the improved technique enables a system to activate the element to which a determined region is selected. In some implementations, the system makes the determination using a classification engine including a convolutional neural network; such an engine takes as input images of the user's eye and outputs a list of probabilities that the gaze is directed to each of the regions.

Abstract: Techniques of tracking a user's gaze includes identifying a region of a display at which a gaze of a user is directed, the region including a plurality of pixels. By determining a region rather than a point, when the regions correspond to elements of a user interface, the improved technique enables a system to activate the element to which a determined region is selected. In some implementations, the system makes the determination using a classification engine including a convolutional neural network; such an engine takes as input images of the user's eye and outputs a list of probabilities that the gaze is directed to each of the regions.

Abstract: Systems, methods, and computer program products are described for receiving a request for a head pose prediction for an augmented reality experience, identifying at least one positional indicator and at least one rotational indicator associated with the augmented reality experience, and providing the at least one positional indicator and the at least one rotational indicator to a Recurrent Neural Network (RNN) comprising a plurality of cells. The RNN may include a plurality of recurrent steps that each include at least one of the plurality of cells and at least one fully connected (FC) layer. The RNN may be used to generate at least one pose prediction corresponding to head pose changes for the augmented reality experience for at least one upcoming time period, provide the at least one pose prediction and trigger display of augmented reality content based on the at least one pose prediction.

Abstract: Systems, methods, and computer program products are described for receiving a request for a head pose prediction for an augmented reality experience, identifying at least one positional indicator and at least one rotational indicator associated with the augmented reality experience, and providing the at least one positional indicator and the at least one rotational indicator to a Recurrent Neural Network (RNN) comprising a plurality of cells. The RNN may include a plurality of recurrent steps that each include at least one of the plurality of cells and at least one fully connected (FC) layer. The RNN may be used to generate at least one pose prediction corresponding to head pose changes for the augmented reality experience for at least one upcoming time period, provide the at least one pose prediction and trigger display of augmented reality content based on the at least one pose prediction.

Abstract: A near-eye display device reduces vergence accommodation conflict by adjusting a tilt and/or distance of a focal plane of a display panel based on scene depth statistics. For example, many three-dimensional (3D) scenes have closer objects in the lower visual field and farther objects in the upper visual field. Changing the tilt of the focal plane of the display panel to match average 3D screen depths reduces the discrepancy between vergence and accommodation distances. In some embodiments, the near-eye display device employs a fixed tilt of the display panel to match average scene depth statistics across a variety of scenes. In some embodiments, the near-eye display device dynamically adjusts the pitch and yaw of the focal plane of the display panel to match scene statistics for a given scene.