Intel Corporation

Apple Inc.

Osram Sylvania Inc.

Google Inc.

Qiong Huang

Alexey Supikov

Ronald T Azuma

Branko Petljanski

Joshua J Ratcliff

Joseph Allen Olsen

Edward Allen Valko

Tuotuo Li

John N Border

Tuan Anh Nguyen

Ming Chu Li

Paul Winer

Yuan Yuan

Anders Grunnet-Jepsen

Emanuele Mandelli

Noah Denis Bedard

Martin Haller

Ofir Mulla

Yi Yang

Keenan Molner

Gabriel Leblanc

William A Truong

Alexey Galata

Yixing Cai

Phil M Hobson

Hyungryul J Choi

Graham Butler Myhre

Richard Speer

Michael Quilici

Bruce Radl

Zhuo Wang

Tom Sengelaub

Kathrin Berkner-Cieslicki

Paul V Johnson

Hua Gao

Victoria C Chan

Douglas Harriott

Nan Zhu

Rodrigo Pereyra

Tzu-Chan Chuang

Christina G Gambacorta

William W Sprague

Elijah H Kleeman

Brandon E Clarke

Seung Cheo Ryu

Andrei Nikiforov

Qi Dai

Hot word free adaptation, of function(s) of an automated assistant, responsive to determining, based on gaze measure(s) and/or active speech measure(s), that a user is engaging with the automated assistant. Implementations relate to techniques for mitigating false positive occurrences of and/or false negative occurrences, of hot word free adaptation, through utilization of a permissive parameter set in some situation(s) and a restrictive parameter set in other situation(s). For example, utilizing the restrictive parameter set when it is determined that a user is engaged in conversation with additional user(s). The permissive parameter set includes permissive parameter(s) that are more permissive than counterpart(s) in the restrictive parameter set. A parameter set is utilized in determining whether condition(s) are satisfied, where those condition(s), if satisfied, indicate that the user is engaging in hot word free interaction with the automated assistant and result in adaptation of function(s) of the automated assistant.

Dynamic adaptation of parameter set used in hot word free adaptation of automated assistant

In one implementation, an apparatus includes: a display to emit light in a first wavelength range; one or more light sources to emit light in a second wavelength range; a camera to detect the light in the second wavelength range; and an eyepiece to reflect and refract the light in the first wavelength range while passing, without substantial distortion, the light in the second wavelength range, wherein the eyepiece includes two lens halves separated by a retarder that changes light in the first wavelength range from a first polarization to a second polarization different from the first polarization.

Method and device for image display and eye tracking through a catadioptric lens

Disclosed herein are systems, apparatus, methods, and articles of manufacture to present three dimensional images without glasses. An example apparatus includes a micro lens array and at least one processor. The at least one processor is to: determine a first position of a first pupil of a viewer; determine a second position of a second pupil of the viewer; align a first eye box with the first position of the first pupil; align a second eye box with the second position of the second pupil; render, for presentation on a display, at least one of a color plus depth image or a light field image based on the first position of the first pupil and the second position of the second pupil; and cause backlight to be steered through the micro lens array and alternatingly through the first eye box and the second eye box.

Three dimensional glasses free light field display using eye location

Techniques related to generating holographic images for a holographic heads up display are discussed. Such techniques include application of a machine learning model to the target image to generate data that is used to enable the determination of a phase pattern via an iterative propagation feedback model. The iterative propagation feedback model is used to generate a feedback strength value, which is then used to generate a phase diffraction pattern for presentation at a holographic plane of the heads up display.

Real time holography using learned error feedback

A head-mounted display may include a display system and an optical system in a housing. The display system may have displays that produce images. Positioners may be used to move the displays relative to the eye positions of a user's eyes. An adjustable optical system may include tunable lenses such as tunable cylindrical liquid crystal lenses. The displays may be viewed through the lenses when the user's eyes are at the eye positions. A sensor may be incorporated into the head-mounted display to measure refractive errors in the user's eyes. The sensor may include waveguides and volume holograms, and a camera for gathering light that has reflected from the retinas of the user's eyes. Viewing comfort may be enhanced by adjusting display positions relative to the eye positions and/or by adjusting lens settings based on the content being presented on the display and/or measured refractive errors.

Head-mounted display device with vision correction

Methods and apparatus for using polarized light (e.g., infrared (IR) light) to improve eye-related functions such as iris recognition. An eye camera system includes one or more IR cameras that capture images of the user's eyes that are processed to perform iris recognition, gaze tracking, or other functions. At least one polarizing element may be located in the path of the light which is used to capture images of the user's eye. The user's eye may be illuminated by IR light emitted by one or more LEDs. At least one of the LEDs may be an LED with a polarizing filter. Instead or in addition, at least one polarizer may be located at the eye camera sensor, in the eye camera optics, or as or in an additional optical element located on the light path between the eye camera and the user's eye.

Eye camera systems with polarized light

Techniques related to generating holographic images are discussed. Such techniques include application of a hybrid system including a pre-trained deep neural network and a subsequent iterative process using a suitable propagation model to generate diffraction pattern image data for a target holographic image such that the diffraction pattern image data is to generate a holographic image when implemented via a holographic display.

Deep computational holography

Techniques related to generating holographic images are discussed. Such techniques include application of a machine learning model to the target image to generate data that is used to enable the determination of a phase pattern via an iterative propagation feedback model. The iterative propagation feedback model is used to generate a feedback strength value, which is then used to generate a phase diffraction pattern for presentation at a holographic plane.

Techniques related to generating holographic images are discussed. Such techniques include application of a machine learning model to the target image to generate data that is used to enable the determination of a phase pattern via a wave propagation model. The wave propagation model is used to generate holographic data, which is then adjusted according to one or more constraints associated with the holographic display that will be used to generate a holographic image based on the adjusted holographic data.

Techniques related to generating holographic images are discussed. Such techniques include application of a hybrid system including a pre-trained deep neural network and a subsequent iterative process using a sui table propagation model to generate diffraction pattern image data for a target holographic image such that the diffraction pattern image data is to generate a holographic image when implemented via a holographic display.

Techniques related to generating holographic images are discussed. Such techniques include application of a pre-trained deep neural network to a target holographic image to generate a feedback strength value for error feedback in an iterative propagation feedback model and generating a diffraction pattern image corresponding to the target holographic image by applying the iterative propagation feedback model based on the target holographic image and using the feedback strength value.

Methods and apparatus for fabricating light-emitting diodes (LEDs) that include polarizing or wavefront-altering optical components are described in which additional optical components are added to the LED package to filter or modify the polarization of the emitted photons. Packaged LEDs that include polarizing or wavefront-altering optical components are also described. The packaged LEDs may emit infrared light that is polarized or otherwise altered by the optical components added during the fabrication process.

Light-emitting diodes with optical filters

In one implementation, an apparatus includes a display to emit light in a first wavelength range, a camera to detect light in a second wavelength range, an eyepiece to distort light in the first wavelength range, and one or more light sources, disposed between the eyepiece and the display, to emit light in the second wavelength range. In one implementation, an apparatus includes a display to emit light in a first wavelength range, one or more light sources to emit light in a second wavelength range, a camera to detect light in a second wavelength range, and an eyepiece to reflect and refract light in the first wavelength range while passing, without substantial distortion, light in the second wavelength range.

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San Jose, CA, United States of America

Qiong Huang