Intel Corporation

Ronald T Azuma

Alexey Supikov

Qiong Huang

Joshua J Ratcliff

Tuotuo Li

Sabine Roessel

Paul Winer

Anders Grunnet-Jepsen

Ofir Mulla

Mario Palumbo

Oscar Nestares

Yan Xu

Ginni Grover

Gheric Speiginer

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

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.

Thin, multi-focal plane, augmented reality eyewear are disclosed. An example lens structure includes a two-layer waveguide including a first waveguide and a second waveguide. The two-layer waveguide produces a virtual object based on light from an image source. The two-layer waveguide causes the virtual object to appear at a first virtual object focal plane. The first waveguide propagates more of the light in a first wavelength range than in a second wavelength range. The second waveguide propagates more of the light in the second wavelength range than in the first wavelength range. The first wavelength range is associated with longer wavelengths than the second wavelength range. The lens structure further includes an optical lens to cause the virtual object to appear at a second virtual object focal plane associated with a shorter apparent distance from a user than the first virtual object focal plane.

Thin, multi-focal plane, augmented reality eyewear

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.

Disclosed herein is display stacks for virtual reality (VR) displays arranged to present an image where a focal point of the image is presented in higher resolution than a periphery around the focal point. The disclosure provides systems and methods for presenting an image comprising a high resolution having a smaller field of view than that with which a lower resolution image is presented around a periphery of the high resolution image.

Foveated virtual reality near eye displays

In some examples, a three dimensional display system includes a display (for example, a display screen or a display panel), a micro lens array, and an eye tracker to track one or more eyes of a person and to provide eye location information. The display system also includes a rendering processor to render or capture color plus depth images (for example, RGB-D images) or light field images. The display system also includes a light field processor to use the eye location information to convert the rendered color plus depth images or light field images to display images to be provided to the display.

The present disclosure is directed to systems and methods for providing an augmented reality system having one or more optical structures capable of resolving virtual objects on one or more virtual object focal planes while providing a sufficient level of transmittivity and optical correction to simultaneously resolve real-world, physical, objects. The lens structures include a plurality of waveguide layers including waveguide layers demonstrating red-green sensitivity and waveguide layers demonstrating blue-green sensitivity. One or more plano-concave lenses may be used to draw virtual objects from a relatively distant first virtual object focal plane to a relatively closer second virtual object focal plane. One or more plano-convex lenses may be used to cause physical objects to appear at a distance from the augmented reality eyewear system approximately equal to the second virtual object focal plane.

A mechanism is described for facilitating true three-dimensional (3D) virtual imaging on computing devices. A method of embodiments, as described herein, includes computing a virtual 3D model corresponding to an object. The method may further include computing and projecting, based the virtual 3D model, a unified surface image of the object via a dynamic 3D shape component, and generating and rendering a virtual image of the object based on the unified surface image such that the virtual image is capable of floating in air.

Facilitating true three-dimensional virtual representation of real objects using dynamic three-dimensional shapes

Embodiments for image capture feedback are disclosed. In some embodiments, a computing system may receive a first image from an image capture device and generate a score for the first image. The computing system may generate a recommendation for an action, such that if the image capture device captures a second image after the action is performed, the score for the second image will be better than the score for the first image. The computing system may indicate the recommended action to the user on an output device. Other embodiments may be disclosed and/or claimed.

Growing community of inventors

San Jose, CA, United States of America

Ronald T Azuma