Google Inc.

Xu Han

Adarsh Prakash Murthy Kowdle

Zhijun He

Ruben Manuel Velarde

Shahram Izadi

Lu Gao

Clayton Kimber

Wen Yu Chien

Gopal Parupudi

Jae Min Purvis

Po-Jen Chang

Kourosh Derakshan

This disclosure describes systems and techniques for synchronizing cameras and tagging images for face authentication. For face authentication by a facial recognition model, a dual infrared camera may generate an image stream by alternating between capturing a 'flood image' and a “dot image” and tagging each image with metadata that indicates whether the image is a flood or a dot image. Accurately tagging images can be difficult due to dropped frames and errors in metadata tags. The disclosed systems and techniques provide for the improved synchronization of cameras and tagging of images to promote accurate facial recognition.

Camera synchronization and image tagging for face authentication

This document describes techniques and systems that enable automatic exposure and gain control for face authentication. The techniques and systems include a user device initializing a gain for a near-infrared camera system using a default gain. The user device ascertains patch-mean statistics of one or more regions-of-interest of a most-recently captured image that was captured by the near-infrared camera system. The user device computes an update in the initialized gain to provide an updated gain that is usable to scale the one or more regions-of-interest toward a target mean-luminance value. The user device dampens the updated gain by using hysteresis. Then, the user device sets the initialized gain for the near-infrared camera system to the dampened updated gain.

Automatic exposure and gain control for face authentication

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Mountain View, CA, United States of America

Xu Han