Google Inc.

Juston Payne

Aaron Michael Donsbach

Maj Isabelle Olsson

John Lapetina

Blaise Hilary Aguera-Arcas

Daniel Ramage

Krzysztof Duleba

Kenneth Sweet

Jon Gabriel Clapper

Alison Lentz

Benjamin Vanik

Jess Holbrook

Joshua Denali Lovejoy

Emily Anne Fortuna

Oliver Fritz Lange

Eva Ariella Siobhan Snee

Iwona Bialynicka-Birula

Michael Robert Arens

Li Zhang

Hugh Brendan McMahan

Tressa Christie Scott

Natalie Naruns

Robert Douglas Fritz, Iii

Dong Rim Lee

Matthew Donald Wilson

Peter Michael Cazalet

Jason Stanley Pi

Philip Dam Roadley-Battin

Benjamin J McMahan

Kai Sun Yick

Jonathan Yoshida Rowell

Divya Tyamagundlu

Joshua Randall Clyne

Jade Daniel Moreau

Kristine Kohlhepp

Dongeek Shin

Steven Benjamin Goldberg

Michael John Schoenberg

Shiblee Imtiaz Hasan

Jingying Hu

Xiuxiu Yuan

A method including generating two or more audio signals (e.g., by two or more microphones) based on a user interaction with a wearable device, generating an audio signature based on the two or more audio signals, and identifying at least one of a coordinate or a gesture based on an output of a machine-learned model given the audio signature.

Detecting input gestures using onboard microphones

Techniques of displaying content on a transparent display include detecting an individual present with respect to a world side, i.e., facing away from a user of a transparent display, opposite side of the transparent display as the user side. For example, circuitry connected to smartglasses detects the presence of an individual in the vicinity of the world side of a transparent display. In response, the circuitry causes an image of the individual to be generated and, based on the image, the circuitry classifies the individual as being in a state satisfying a set of criteria or not. In some implementations, the set of criteria include the individual being oriented in such a way as to be able to see the document. In response to the individual satisfying the criteria, the circuitry obscures the document from the view of the individual.

Reducing light leakage via external gaze detection

The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. In particular, the present disclosure provides low power frameworks for controlling image sensor mode in a mobile image capture device. On example low power frame work includes a scene analyzer that analyzes a scene depicted by a first image and, based at least in part on such analysis, causes an image sensor control signal to be provided to an image sensor to adjust at least one of the frame rate and the resolution of the image sensor.

Low power framework for controlling image sensor mode in a mobile image capture device

The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. The mobile image capture device is operable to input an image into at least one neural network and to receive at least one descriptor of the desirability of a scene depicted by the image as an output of the at least one neural network. The mobile image capture device is operable to determine, based at least in part on the at least one descriptor of the desirability of the scene of the image, whether to store a second copy of such image and/or one or more contemporaneously captured images in a non-volatile memory of the mobile image capture device or to discard a first copy of such image from a temporary image buffer without storing the second copy of such image in the non-volatile memory.

Systems and methods for selective retention and editing of images captured by mobile image capture device

Image device holder

Image capture device

Image capture device holder

The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. The mobile image capture device is operable to input an image into at least one neural network and to receive at least one descriptor of the desirability of a scene depicted by the image as an output of the at least one neural network. The mobile image capture device is operable to determine, based at least in part on the at least one descriptor of the desirability of the scene of the image, whether to store a second copy of such image in a non-volatile memory of the mobile image capture device or to discard a first copy of such image from a temporary image buffer without storing the second copy of such image in the non-volatile memory.

Systems and methods that leverage deep learning to selectively store images at a mobile image capture device

Growing community of inventors

San Mateo, CA, United States of America

Juston Payne