Microsoft Technology Licensing, LLC

Christopher Charles Aholt

Joel Steven Kollin

Robert Thomas Held

Benjamin Eliot Lundell

Andreas Georgiou

Ishan Chatterjee

Maria Esther Pace

Christopher Maurice Mei

Paulo Ricardo Dos Santos Mendonca

Rayna Demaster-Smith

Mark Theodore Bolas

Bernard Charles Kress

Steven John Robbins

Navid Poulad

Jessie Cindy Maikim

Curtis Alan Tesdahl

David Rohn

Andrew Kilgour Juenger

James Peele Terrell, Jr

Marko Bezulj

Nicholas Mark Cirucci

Jordan Christopher Jur

Richard Zachary Robinson

One disclosed example provides a near-eye display device. The near-eye display device comprises an eye tracking system configured to determine a position of an eye of a user relative to the near-eye display device, and a waveguide including at least an input coupler and an output coupler, the output coupler including a plurality of zones, each zone activatable via a dynamically controllable output coupling element of the zone. The near-eye display device further comprises an image source configured to output image light to the input coupler, and a controller configured to selectively activate one or more zones of the output coupler based at least on the position of the eye.

Dynamic control of waveguide eye box

The disclosed techniques provide enhanced eye tracking systems utilizing joint estimation of biological parameters and hardware parameters. A system uses joint estimation of biological parameters, e.g., direction and position of an eye, with concurrent estimation of hardware parameters, e.g., camera position or camera direction, to self-calibrate and provide eye tracking estimations to accommodate for deformations and other changes of a device. Sensor data is used to select hardware parameters of a camera for use in the joint estimation with the biological parameters, where the hardware parameters are estimated based on glint and pupil position of a user. The disclosed techniques include a method to model changes of a device, as well as detect and compensate for them while the eye-tracking device is in normal use, without requiring a factory-calibration procedure to be repeated.

Enhanced eye tracking systems utilizing joint biological and hardware estimations

A gaze detection assembly comprises a plurality of infrared (IR) light emitters configured to emit IR light toward a user eye and an IR camera configured to sequentially capture IR images of the user eye. A controller is configured to, during a reference frame, control the plurality of IR light emitters to emit IR light toward the user eye with a reference intensity distribution. During the reference frame, an IR image is captured depicting a first glint distribution on the user eye. Based at least in part on the first glint distribution, during a subsequent frame, the plurality of IR light emitters are controlled to emit IR light toward the user eye with a subsequent intensity distribution, different than the reference intensity distribution. During the subsequent frame, a second IR image is captured depicting a second glint distribution on the user eye.

Variable intensity distributions for gaze detection assembly

A device includes a frame configured to be supported in front of a user eye. The frame has a first side facing the user eye and a second side opposite the first side and facing an environment. A light emitting diode is supported by the frame to emit light. The light emitting diode is obscured by an opaque material from an observer in front of the user in the environment. A light deflector is supported by the frame to direct the emitted light from the light emitting diode towards the user eye.

Head mounted display with obscured light emitting diodes

Examples are disclosed that relate to using an array of hot mirrors in an eye-imaging system. One example provides a head-mounted display system, comprising a frame, an eye-imaging camera supported on the frame, a switchable hot mirror array comprising a plurality of switchable hot mirrors configured to direct light reflecting from an eye toward the eye-imaging camera, and a controller configured to control switching of a reflectivity of each of the plurality of switchable hot mirrors.

Eye-imaging system with switchable hot mirrors

A computer-implemented method of field calibrating a device is disclosed. In one example, a reference image is acquired, via an infrared camera, while the device is in a factory-calibrated state. The reference image measures a factory-calibrated spatial relationship of one or more infrared-visible fiducial markers of the device relative to the infrared camera while the device is in the factory-calibrated state. Later, a field image is acquired, via the infrared camera. The field image measures an updated spatial relationship of the one or more infrared-visible fiducial markers relative to the infrared camera. The device is field calibrated based on the reference image and the field image.

Fiducial marker based field calibration of a device

A color correction mask programmatically generated in software on an HMD device is applied to a gaze region on a display field of view (FOV) on a head-mounted display (HMD) device to optimize system resources while rendering a display. Eye monitoring sensors are utilized to track movement of a user's eyes while the user operates the HMD device to determine a gaze position of the user's eyes on the display FOV. Using the determined gaze position, a dynamic foveal gaze region is sized around the gaze position so that the foveal portion of the display FOV is color-corrected, that is, color non-uniformities are reduced or eliminated. In other implementations, a gaze-based weighting mode is implemented in which measurements of the user's full eye or eye orbit are utilized to color correct a larger surface area of the display FOV relative to the foveal color correction mode.

Foveated color correction to improve color uniformity of head-mounted displays

The disclosure herein describes controlling focal parameters of a head mounted display based on an estimated user age to account for increasing likelihood of presbyopia as user age increases. The head mounted display uses eye tracking sensors to collect ocular metric data associated with ocular features of a user's eye and a user age estimate is calculated based on analysis of the ocular metric data using a machine learning algorithm and an ocular metric data set. Further, a confidence value of the user age estimate is calculated based on the analysis of the ocular metric data. Then, focal parameters of the visual display of the head mounted display are controlled based on the user age estimate and confidence value. The described focal control method provides a seamless, automated way for a head mounted display system to adjust settings to provide a sharp, in-focus user experience for users of all ages.

Controlling focal parameters of a head mounted display based on estimated user age

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Newcastle, WA, United States of America

Christopher Charles Aholt