Google Inc.

Iwona Bialynicka-Birula

Aaron Michael Donsbach

Blaise Hilary Aguera-Arcas

Daniel Ramage

Krzysztof Duleba

Jon Gabriel Clapper

Juston Payne

Alison Lentz

Benjamin Vanik

Jess Holbrook

Joshua Denali Lovejoy

Emily Anne Fortuna

Oliver Fritz Lange

Li Zhang

Hugh Brendan McMahan

Robert Douglas Fritz, Iii

Benjamin J McMahan

Divya Tyamagundlu

Kristine Kohlhepp

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

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

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Redmond, WA, United States of America

Iwona Bialynicka-Birula