Microsoft Technology Licensing, LLC

Hewlett-packard Company

David Rohn

Curtis Alan Tesdahl

Benjamin Eliot Lundell

Andrew Clark Goris

Scott Fullam

Dmitry Reshidko

Brian L Hastings

Lev Cherkashin

James Tichenor

Steven James Velat

Dmitriy Churin

Travis Scott Legg

Craig Haskins

Lori Ann Potts

Aswathi Sudhir

Sayyed Jaffar Ali Raza

Kevin James Matherson

David Douglas Bohn

Thomas Charles Oliver

Derek L Knee

Navid Poulad

Eugene Arthur Miksch

Christopher Charles Aholt

Randall T Crane

James Peele Terrell, Jr

Marko Bezulj

Justin E Forrester

James Peele Terrell

Scott Francis Fullam

Eye and hand tracking systems in head-mounted display (HMD) devices are arranged with lensless camera systems using optical masks as encoding elements that apply convolutions to optical images of body parts (e.g., eyes or hands) of HMD device users. The convolved body images are scrambled or coded representations that are captured by a sensor in the system, but are not human-recognizable. A machine learning system such as a neural network is configured to extract body features directly from the coded representation without performance of deconvolutions conventionally utilized to reconstruct the original body images in human-recognizable form. The extracted body features are utilized by the respective eye or hand tracking systems to output relevant tracking data for the user's eyes or hands which may be utilized by the HMD device to support various applications and user experiences. The lensless camera and machine learning system are jointly optimizable on an end-to-end basis.

Eye and hand tracking utilizing lensless camera and machine learning

Eye-tracking systems and methods utilize transparent illumination structures having a plurality of IR μLEDs distributed with a predetermined pattern within the transparent viewing area of illumination structures. The μLEDs are small enough that they are not visible by a user during use of an HMD or other mixed-reality device, for example, such that they can be positioned within the line-of-sight of the user through the illumination structure and without visibly obscuring or interfering with the user's view of the mixed-reality environment by the mixed-reality device.

Method for manufacturing a microLED based illumination structure comprising infrared micro light emitting devices

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

Eye-tracking systems and methods utilize transparent illumination structures having a plurality of IR &#x3bc;LEDs distributed within the transparent viewing area of illumination structures. The &#x3bc;LEDs are small enough (&#x3c;100 &#x3bc;m) that they are not visible by a user during use of an HMD or other mixed-reality device, for example, such that they can be positioned within the line-of-sight of the user through the illumination structure and without visibly obscuring or interfering with the user's view of the mixed-reality environment by the mixed-reality device.

Infrared microled based invisible illumination for eye tracking

Examples of mixed reality computing devices that utilize remote sensors and local sensors as input devices are disclosed. In one example, a mixed reality computing device comprises an image sensor, a remote input device, a processor, and storage comprising stored instructions. The stored instructions are executable by the processor to perform object motion tracking and environmental tracking based on output from the image sensor, and in response to detecting that the remote input device is in use, adjust a parameter of the motion tracking while maintaining the environmental tracking.

Object motion tracking with remote device

In embodiments, an encoded micro pattern includes segments of encoded bits that can be optically-imaged by a digitizer. The position of each segment in the encoded micro pattern can be determined from the encoded bits in a segment. Each of the segments of the encoded micro pattern also includes a fiducial marker that indicates an orientation of a segment in the encoded pattern. The encoded bits of the encoded micro pattern can be integrated into a display surface of a display device, or integrated in a display screen that is positioned over the display surface of a display device.

Encoded micro pattern

A scanning device includes a mode for generating a reproduced image on a standard page size from a large-sized original image. In this mode, the sampling rate of the scanning device in a motion direction is reduced. In addition, the captured image data in the sensor direction is downsampled by some factor. Position data that is generated as the image data is captured is also modified in accordance with the downsampling factor. A reproduced image is then generated from the modified image and position data and printed at a standard resolution.

Method and system for capturing large format documents using a portable hand-held scanner

Edge to edge image sensor and navigator for portable scanner

Growing community of inventors

Fort Collins, CO, United States of America

David Rohn