Apple Inc.

Intel Corporation

Other

Mohamed Selim Ben Himane

Daniel R Kurz

Peter Meier

Anselm Grundhoefer

Haowei Liu

Raffi A Bedikian

Arun Srivatsan Rangaprasad

Vincent Chapdelaine-Couture

Thomas Olszamowski

Samer Samir Barakat

Moinul H Khan

Lejing Wang

Thomas G Salter

Tom Sengelaub

Jeffrey S Norris

Pedro Manuel Da Silva Quelhas

Paul Ewers

Brian Chris Clark

Scott G Wade

Daniel Joseph Mirota

Katharina Buckl

Jim Chen Chou

Ian M Richter

Timothy Robert Oriol

Michele Stoppa

Adam Michael O'Hern

Leonid Keselman

Jean-Charles Bernard Marcel Bazin

Waleed Abdulla

Shubham Agrawal

Sree Harsha Kalli

Hon Pong Ho

Duc Q Pham

Joseph M Luxton

Dhruv A Govil

Anselm Grundhöfer

Julien Monat Rodier

Eddie G Mendoza

Various implementations disclosed herein include devices, systems, and methods that provide detecting and decoding of visual markers that encode data. In some implementations, a visual marker is detected in an image of a physical environment. In some implementations, detecting the visual marker is based on a pre-determined portion of the visual marker. In some implementations, detecting the visual marker is based on a predefined shape. In some implementations, a visual marker interpretation scheme is determined for decoding the visual marker. In some implementations, the visual marker is decoded based on one or more colors being attributed a same value. In some implementations, the visual marker is decoded based on one or more other colors being attributed a different value.

Visual marker with user selectable appearance

Various implementations disclosed herein include devices, systems, and methods that provide a visual marker including a plurality of markings arranged in a corresponding plurality of shapes. In some implementations, each marking is formed of a set of sub-markings separated by gaps and arranged according to a respective shape, and the gaps of the plurality of markings are configured to encode data and indicate orientation of the visual marker. In some implementations, the plurality of markings are arranged in a plurality of concentric rings of increasing size. In some implementations, the orientation is encoded in a first set of gaps and data in a second set of gaps of the gaps in the plurality of markings.

Visual marker

Identifying a specular surface, such as a mirror, in a captured scene includes extracting, from one or more images of the scene, a set of natural features and generating, from the image, a set of synthesized 'mirrored' features. One or more correspondences may be determined between the set of natural features in the image and the set of synthesized mirrored features. A first set of features are identified based on the determined one or more correspondences as representing a specular surface (e.g., a mirror) located in the scene, and then a geometry and/or location of the specular surface within the scene may be determined. For example, in some embodiments, the feature from a determined pair of corresponding features in a scene that is determined to be farther away from the device that captured the image(s) of the scene may be determined to be the feature lying on the specular surface.

Detecting specular surfaces

Some implementations provide improved user interfaces for interacting with a virtual environment. The virtual environment is presented by a display of a first device having an image sensor. The first device uses the image sensor to determine a relative position and orientation of a second device based on a marker displayed on a display of the second device. The first device uses the determined relative position of the second device to display a representation of the second device including virtual content in place of the marker.

Tracking and drift correction

Various implementations disclosed herein include devices, systems, and methods that provide color visual markers that include colored markings that encode data, where the colors of the colored markings are determined by scanning (e.g., detecting the visual marker using a sensor of an electronic device) the visual marker itself. In some implementations, a visual marker is detected in an image of a physical environment. In some implementations, the visual marker is detected in the image by detecting a predefined shape of a first portion of the visual marker in the image. Then, a color-interpretation scheme is determined for interpreting colored markings of the visual marker that encode data by identifying a set of colors at a corresponding set of predetermined locations on the visual marker. Then, the data of the visual marker is decoded using the colored markings and the set of colors of the color-interpretation scheme.

Various implementations disclosed herein include devices, systems, and methods that detect surfaces and reflections in such surfaces. Some implementations involve providing a CGR environment that includes virtual content that replaces the appearance of a user or the user's device in a mirror or other surface providing a reflection. For example, a CGR environment may be modified to include a reflection of the user that does not include the device that the user is holding or wearing. In another example, the CGR environment is modified so that virtual content, such as a newer version of the electronic device or a virtual wand, replaces the electronic device in the reflection. In another example, the CGR environment is modified so that virtual content, such as a user avatar, replaces the user in the reflection.

Image-based detection of surfaces that provide specular reflections and reflection modification

Methods, systems, and computer readable media for providing personalized saliency models, e.g., for use in mixed reality environments, are disclosed herein, comprising: obtaining, from a server, a first saliency model for the characterization of captured images, wherein the first saliency model represents a global saliency model; capturing a first plurality of images by a first device; obtaining information indicative of a reaction of a first user of the first device to the capture of one or more images of the first plurality images; updating the first saliency model based, at least in part, on the obtained information to form a personalized, second saliency model; and transmitting at least a portion of the second saliency model to the server for inclusion into the global saliency model. In some embodiments, a user's personalized (i.e., updated) saliency model may be used to modify one or more characteristics of at least one subsequently captured image.

Systems and methods for providing personalized saliency models

A method includes tracking, via a positional tracker, the paired peripheral input device in a first tracking mode. The method includes obtaining sensor data from the paired peripheral input device via a communication interface. The method includes determining that the paired peripheral input device satisfies a contact criterion based on the sensor data. The contact criterion is based on a contact between the paired peripheral input device and a physical object. The method includes, in response to determining that the paired peripheral input device satisfies the contact criterion, changing the positional tracker from the first tracking mode to a second tracking mode. Tracking in the second tracking mode is based in part on a depth that indicates a distance between the electronic device and the physical object.

Tracking a paired peripheral input device based on a contact criterion

The present disclosure relates generally to localization and mapping. In some examples, an electronic device obtains first image data and motion data using a motion sensor. The electronic device receives information corresponding to a second electronic device. The electronic device generates a representation of a first pose of the first electronic device using the first image data, the motion data, and the information corresponding to the second electronic device. The electronic device displays, on the display, a virtual object, wherein the displaying of the virtual object is based on the representation of the first pose of the first electronic device.

Localization and mapping using images from multiple devices

A method of projecting digital information on a real object in a real environment includes the steps of projecting digital information on a real object or part of a real object with a visible light projector, capturing at least one image of the real object with the projected digital information using a camera, providing a depth sensor registered with the camera, the depth sensor capturing depth data of the real object or part of the real object, and calculating a spatial transformation between the visible light projector and the real object based on the at least one image and the depth data. The invention is also concerned with a corresponding system.

Method of and system for projecting digital information on a real object in a real environment

One exemplary implementation facilitates object detection using multiple scans of an object in different lighting conditions. For example, a first scan of the object can be created by capturing images of the object by moving an image sensor on a first path in a first lighting condition, e.g., bright lighting. A second scan of the object can then be created by capturing additional images of the object by moving the image sensor on a second path in a second lighting condition, e.g., dim lighting. Implementations determine a transform that associates the scan data from these multiple scans to one another and use the transforms to generate a 3D model of the object in a single coordinate system. Augmented content can be positioned relative to that object in the single coordinate system and thus will be displayed in the appropriate location regardless of the lighting condition in which the physical object is later detected.

Object detection using multiple three dimensional scans

Implementations use a first device (e.g., an HMD) to provide a CGR environment that augments the input and output capabilities of a second device, e.g., a laptop, smart speaker, etc. In some implementations, the first device communicates with a second device in its proximate physical environment to exchange input or output data. For example, an HMD may capture an image of a physical environment that includes a laptop. The HMD may detect the laptop, send a request the laptop's content, receive content from the laptop (e.g., the content that the laptop is currently displaying and additional content), identify the location of the laptop, and display a virtual object with the received content in the CGR environment on or near the laptop. The size, shape, orientation, or position of the virtual object (e.g., a virtual monitor or monitor extension) may also be configured to provide a better user experience.

Augmented devices

A method includes obtaining an image via an image sensor, and identifying, within the image, a physical object represented by a portion of the image. The method includes determining, based on the image, a visual feature characterizing the physical object. The method includes warping, based on the visual feature satisfying a first feature criterion, the portion of the image according to a first warping function that is based on the first feature criterion and a distance between the electronic device and a reference point. The method includes warping, based on the visual feature satisfying a second feature criterion that is different from the first feature criterion, the portion of the image according to a second warping function that is based on the second feature criterion and the distance between the electronic device and the reference point.

Adaptive image warping based on object and distance information

Touch detection using a mirror accessory may include obtaining first image data comprising a touching object and a target surface, wherein the first image data captures a scene comprising the touching object and the target surface from the viewpoint of a camera, obtaining second image data comprising the touching object and the target surface, wherein the second image data captures the touching object and the target surface as a reflection in a mirror that is separate from the target surface, determining a pose of the mirror in the scene, determining a pose of the touching object in the scene based on the first image data, the second image data, and the pose of the mirror, and estimating a touch status between the touching object and the target surface based on the determined pose of the touching object and a pose of the target surface.

Growing community of inventors

Milpitas, CA, United States of America

Mohamed Selim Ben Himane