Google Inc.

Alexander James Faaborg

Austin Robison

Brett Aladdin Barros

Daniel Marc Gatan Shiplacoff

Gabriel Aaron Cohen

Joshua Robin Kaplan

Manuel Christian Clement

Peter Ng

Simon Tickner

Joshua L Weaver

John Nicholas Jitkoff

Henrique Dias Penha

Matias Gonzalo Duarte

Marco Paglia

Chris McKenzie

Shengzhi Wu

Antonio Bernardo Monteiro Costa

Clayton Woodward Bavor, Jr

Angana Ghosh

Gustavo Sonoda

Glen Murphy

Christian Plagemann

Morten Just Petersen

Jon M Wiley

Eliezer Peli

Andrew Theodore Wansley

Michael Steven Feldstein

Michael Arthur Simonian

Randall Sarafa

Richard Zarek Cohen

Peter John Hodgson

Bjorn Erik Bringert

Rahul Garg

Gabor Cselle

Murphy Stein

Andrey Doronichev

Tristan Harris

Luca Zanolin

Christian Robertson

Ariel Benjamin Sachter-Zeltzer

Samuel Kvaalen

Shiqi Chen

Jeffrey Albert Chang

Adrian L Ludwig

Michael John Schoenberg

Emmet J Connolly

Daniel Shiplacoff

Lee Brandon Keely

Jens Nagel

Robert J Greenwalt, Iii

Pawel Pietryka

Robert Carl Jagnow

Adam William Powell

Joost Korngold

Zhaoyang Xu

Scott Dolim

Nicholas Neil Kralevich, Iv

Henrique Penha

Leon Hong

Robbie Tilton

Jonathan Tompson

Thomas Ramon Karlo

Andrew Nartker

Winthrop Lyon Saville, Iii

Andrew Anderson Stewart

Samuel Mark Matson

Leandro Gracia Gil

Jake Hamby

Kankan Meng

Lucas Ochoa

Clayton Woodward Bavor

Joshua Weaver

Jr Clayton Woodward Bavor

Jon Michael Wiley

Daniel Marc Shiplacoff

Andrew Stewart

The present disclosure relates generally to the processing of machine-readable visual encodings in view of contextual information. One embodiment of aspects of the present disclosure comprises obtaining image data descriptive of a scene that includes a machine-readable visual encoding; processing the image data with a first recognition system configured to recognize the machine-readable visual encoding; processing the image data with a second, different recognition system configured to recognize a surrounding portion of the scene that surrounds the machine-readable visual encoding; identifying a stored reference associated with the machine-readable visual encoding based at least in part on one or more first outputs generated by the first recognition system based on the image data and based at least in part on one or more second outputs generated by the second recognition system based on the image data; and performing one or more actions responsive to identification of the stored reference.

Platform for registering and processing visual encodings

According to an aspect, a method of identifying a position of a controllable device includes receiving visual data from an image sensor on a wearable device, generating, by an object recognition module, identification data based on the visual data, and identifying, using the identification data, a first three-dimensional (3D) map from a map database that stores a plurality of 3D maps including the first 3D map and a second 3D map, where the first 3D map is associated with a first controllable device and the second 3D map is associated with a second controllable device. The method includes obtaining a position of the first controllable device in a physical space based on visual positioning data of the first 3D map and rendering a user interface (UI) object on a display in a position that is within a threshold distance of the position of the first controllable device.

Identifying a position of a controllable device using a wearable device

Systems and techniques include using a sensor of a computing device to detect the presence of a first portion of a code, the code including at least the first portion and a second portion, where the first portion of the code is decodable and includes an identifier and the second portion of the code is non-decodable. The computing device recognizes the identifier in the first portion of the code and obtains instructions for decoding the second portion of the code using the identifier and/or data associated with the identifier. The instructions to decode the second portion of the code are processed to generate a decoded second portion of the code. The computing device performs an action defined in the decoded second portion of the code.

Quick response codes

A head-mounted device (HMD) may be used to determine an access request for accessing a device. An identifier identifying the device may be received at the HMD and from the device. By verifying receipt of the identifier at the HMD, and that access rights associated with the HMD enable granting of the access request, the access request may be granted.

Device access using a head-mounted device

Systems and methods are described for authenticating devices. The systems and methods may include detecting, by a sensor on a wearable device, at least one cloud anchor that includes an identifier associated with a network and configured for a physical environment. In response to detecting that a location associated with the at least one cloud anchor is within a threshold distance of the wearable device and detecting that the wearable device has access to the at least one cloud anchor, triggering extraction of the identifier from the at least one cloud anchor. The systems and methods may also include joining the wearable device to the network based on a received authentication corresponding to the extracted identifier.

Leveraging cloud anchors in authentication

According to an aspect, a method includes detecting, by at least one imaging sensor of a wearable device, facial features of an entity, detecting an interactive communication between a user of the wearable device and the entity based on at least image data from the at least one imaging sensor, updating a conversation graph in response to the interactive communication being detected between the user and the entity, and managing content for display on the wearable device based on the conversation graph.

Managing display content on a wearable device using a conversation graph

According to an aspect, a method for sharing a collaborative augmented reality (AR) environment including obtaining, by a sensor system of a first computing system, visual data representing a physical space of an AR environment, where the visual data is used to create a three-dimensional (3D) map of the physical space. The 3D map includes a coordinate space having at least one virtual object added by a user of the first computing system. The method includes broadcasting, by a transducer on the first computing system, an ultrasound signal, where the ultrasound signal includes an identifier associated with the 3D map. The identifier is configured to be detected by a second computing system to join the AR environment.

Triggering a collaborative augmented reality environment using an ultrasound signal

A system and method is provided that provides for the transfer of the execution of content from a user device to an external device for output of the content by the external device. External devices may be detected in a physical space, and identified based on previous connection with the user device, based on a shared network or shared system of connected devices including the user device, based on image information captured by the user device and previously stored anchoring information that identifies the external devices, and the like. An external device may be selected for potential output of the content based on previously stored configuration information associated with the external device including, for example, output capabilities associated with the external device. The identified external device may output the transferred content in response to a user verification input, verifying that the content is to be output by the external device.

System and method for casting content

Gaze data collected from eye gaze tracking performed while training text was read may be used to train at least one layout interpretation model. In this way, the at least one layout interpretation model may be trained to determine current text that includes words arranged according to a layout, process the current text with the at least one layout interpretation model to determine the layout, and output the current text with the words arranged according to the layout.

Text layout interpretation using eye gaze data

A computer-implemented method includes receiving a two-dimensional image of a scene captured by a camera, recognizing one or more objects in the scene depicted in the two-dimensional image, and determining whether the one or more recognized objects have known real-world dimensions. The computer-implemented method further includes determining a depth of at least one recognized object having known real-world dimensions from the camera, and overlaying three-dimensional (3-D) augmented reality content over a display the 2-D image of the scene considering the depth of the at least one recognized object from the camera.

Augmented reality depth detection through object recognition

A method including receiving at least one frame of a video targeted for display on a main display (or within the boundary of the main display), receiving metadata associated with the at least one frame of the video, the metadata being targeted for display on a supplemental display (or outside the boundary of the main display), and formatting the metadata for display on the supplemental display (or outside the boundary of the main display).

Channel layering of video content for augmented reality (AR) or control-based separation

A user may routinely wear or hold more than one computing devices. One of the computing devices may be a head-mounted computing-device configured for augmented reality. The head-mounted computing-device may include a camera. While imaging, the camera can consume power and processing resources that diminish a battery of the head-mounted computing device. To improve a battery life and to enhance a user's privacy, imaging of the camera can be deactivated during periods when the user is not interacting with the head-mounted computing device and activated when the user wishes to interact with the head-mounted computing device. The activation of the camera can be triggered by gestured data collected by a computing device other than the head-mounted computing-device.

Gesture-triggered augmented-reality

Three-dimensional (3D) maps may be generated for different areas based on scans of the areas using sensor(s) of a mobile computing device. During each scan, locations of the mobile computing device can be measured relative to a fixed-positioned smart device using ultra-wideband communication (UWB). The 3D maps for the areas may be registered to the fixed position (i.e., anchor position) of the smart device based on the location measurements acquired during the scan so that the 3D maps can be merged into a combined 3D map. The combined (i.e., merged) 3D map may then be used to facilitate location-specific operation of the mobile computing device or other smart device.

Systems and methods for generating three-dimensional maps of an indoor space

Growing community of inventors

Mountain View, CA, United States of America

Alexander James Faaborg