Meta Platforms, Inc.

Amy Lawson Bearman

Alireza Dirafzoon

Shijun Sun

Ganesh Venkatesh

Rongzhou Shen

Chengyuan Yan

Emily Wang

John Jacob Blakeley

Yilei Li

Christopher E Balmes

Riza Kazemi

Yiming Pu

Ruchir Srivastava

Matthew Dan Feiszli

Jiwen Ren

Qian Fang

Gabrielle Catherine Moskey

Babak Damavandi

Guangqiang Dong

In one embodiment, a method includes accessing from a client system associated with a first user sensor signals captured by sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the sensors signals are accessed from the sensors based on cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor, detecting a change in a context of the first user associated with an activity of the first user based on machine-learning models and the sensor signals, wherein the change in the context of the first user satisfies a trigger condition associated with the activity, and responsive to the detected change in the context of the first user automatically capturing visual data by cameras of the client system.

Auto-capture of interesting moments by assistant systems

In one embodiment, a method includes receiving touch inputs from a user corresponding to an activation trigger for an assistant system executing on a head-mounted device at the head-mounted device, accessing signals from inertial measurement unit (IMU) sensors of the head-mounted device by the head-mounted device, determining that the user is either donning or doffing the head-mounted device by an on-device don/doff detection model and based only on the signals from the IMU sensors, and overriding the activation trigger to prevent an activation of the assistant system responsive to the received touch inputs.

Preventing false activations based on don/doff detection for assistant systems

In one embodiment, a method includes rendering a first output image comprising one or more augmented-reality (AR) objects for displays of an AR rendering device of an AR system associated with a first user. The method further includes accessing sensor signals associated with the first user. The one or more sensor signals may be captured by sensors of the AR system. The method further includes detecting a change in a context of the first user with respect to a real-world environment based on the sensor signals. The method further includes rendering a second output image comprising the AR objects for the displays of the AR rendering device. One or more of the AR objects may be adapted based on the detected change in the context of the first user.

Dynamic content rendering based on context for AR and assistant systems

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Emerald Hills, CA, United States of America

Amy Lawson Bearman