Google Inc.

Tyler Reed Kugler

Vignesh Sachidanandam

Leonardo Giusti

Brandon Charles Barbello

Alok Chandel

Johan Prag

James Brooks Miller

Selim Flavio Cinek

Lucas Dupin Moreira Costa

Artur Tsurkan

Ivan Poupyrev

Kishore Sundara-Rajan

Debanjan Mukherjee

Philip Quinn

Alexey Polyudov

Patrick M Amihood

John David Jacobs

Devon James O'Reilley Stern

Jung Ook Hong

Abel Seleshi Mengistu

Shumin Zhai

Seungyon Lee

Kelvin Kwong

James Cooper

Isaac William Reynolds

Yun-Ling Lee

Stuart Murray Scott

Kevin Chyn

Devon James O'Reilly Stern

This document describes techniques and systems that enable grid-based enrollment for face authentication. The techniques and systems include overlaying a three-dimensional (3D) tracking window over a preview image of the user's face displayed via a display device. The 3D tracking window includes a plurality of segments, which persist to correspond to an approximate direction that the user's face is facing. Based on the tracking, segments are highlighted to indicate the approximate direction that the user's face is facing, a camera captures enrollment images of the user's face facing that direction, and embeddings are generated based on the enrollment images and stored in a fixed grid of pose cells corresponding to various facial poses for use in face authentication. Responsive to generation and storage of the embeddings, an indication that the one or more segments are completed is provided.

Grid-based enrollment for face authentication

This document describes techniques and systems for authentication management through IMU and radar. The techniques and systems use inertial sensor data from an inertial measurement unit (IMU) and/or radar data to manage authentication for a computing device. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for computing-device authentication.

Authentication management through IMU and radar

This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or 'gate' the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Context-sensitive control of radar-based gesture-recognition

Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Robust radar-based gesture-recognition by user equipment

This document describes techniques and systems that enable radar-based authentication status feedback. A radar field is used to enable an electronic device to account for the user's distal physical cues to determine and maintain an awareness of the user's location and movements around the device. This awareness allows the device to anticipate some of the user's intended interactions and provide functionality in a timely and seamless manner, such as preparing an authentication system to authenticate the user before the user touches or speaks to the device. These features also allow the device to provide visual feedback that can help the user understand that the device is aware of the user's location and movements. In some cases, the feedback is provided using visual elements presented on a display.

Radar-based authentication status feedback

This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor () and/or a movement sensor () produces a context of a user equipment (). The techniques and systems enable the user equipment () to recognize contexts when a radar system () can be unreliable and should not be used for gesture-recognition, enabling the user equipment () to automatically disable or 'gate' the output from the radar system () according to context. The user equipment () prevents the radar system () from transitioning to a high-power state () to perform gesture-recognition in contexts where radar data detected by the radar system () is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Systems and techniques are described for robust radar-based gesture-recognition. A radar system () detects radar-based gestures on behalf of application subscribers. A state machine () transitions between multiple states based on inertial sensor data. A no-gating state () enables the radar system () to output radar-based gestures to application subscribers. The state machine () also includes a soft-gating state () that prevents the radar system () from outputting the radar-based gestures to the application subscribers. A hard-gating state () prevents the radar system () from detecting radar-based gestures altogether. The techniques and systems enable the radar system () to determine when not to perform gesture-recognition, enabling user equipment () to automatically reconfigure the radar system () to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

This document describes techniques and systems for reducing a state based on sensor data from an Inertial Measurement Unit (IMU) and radar. The techniques and systems use inertial sensor data from an IMU as well as radar data to reduce states of a user equipment, such as power, access, and information states. These states represent power used, an amount of access permitted, or an amount of information provided by the user equipment. The techniques manage the user equipment's states to correspond to a user's engagement with the user equipment, which can save power, reduce unwarranted access, and reduce an amount of information provided when the user is not engaged with the user equipment, thereby protecting the user's privacy.

Reducing a state based on IMU and radar

A method includes a processor of an electronic device receiving first input signals from a first sensor in response to user contact at a first edge of the device and second input signals from a second sensor in response to user contact at a second edge of the electronic device. The first and second sensors are covered by a housing of the device. The processor determines an external context of the device based on analysis of the first input signals and the second input signals. The determined external context indicates at least a position of the device relative to a user or an orientation of the device relative to a user. Responsive to determining the external context, the electronic device executes a particular user input action.

Electronic device response to force-sensitive interface

An apparatus utilizes multiple strain gauge ('SG') sensing units which are each disposed adjacent an inner surface of the device housing. Electrical voltage generated by the SGs is amplified by one or more amplifiers to maximize the resolution between a voltage output of an SG when in a non-pressed state and a voltage output of the SG when in a pressed state. Additionally, an electronic circuit is configured to identify a baseline voltage output for an SG over a period of time for comparing to a voltage output for the SG when the SG is in a pressed state such that the pressed state of the SG can be identified by the electronic circuit by comparing a current output voltage of the SG to the identified baseline voltage.

Apparatus for sensing user input

A method includes one or more processors of an electronic device receiving signals from multiple sensors located along an edge of the device. The signals are received in response to external contact being provided to the edge of the device. At least one processor determines a distribution of forces applied to the sensors based on the input signals. Based on the determined distribution of forces, the processor determines: i) a location of the external contact that is offset from a location of each of the multiple sensors, and ii) a magnitude of the force of the external contact. The processor detects whether sensing criteria has been satisfied based on an analysis of: i) the location of the external contact and ii) the magnitude of the force of the external contact. Responsive to detecting that sensing criteria has been satisfied, the processor executes a user input action.

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San Francisco, CA, United States of America

Tyler Reed Kugler