Apple Inc.

Brian Edward Walsh

Marcel Van Os

Jae Woo Chang

Grant R Paul

Nicolas V Scapel

David Robert Black

Xiaohuan Corina Wang

Katherine K Ernst

Gregory L Dudey

Omid Khalili

Jessica L Aboukasm

Christopher G Wilson

William A Sorrentino, Iii

Robert C Chinn

Gregory Evan Niles

Christopher John Moulios

Guido Hucking

Zehang Sun

Kevin M O'Neil

Jean-Francois M Albouze

Greg Dudey

Joseph-Alexander P Weil

Toshihiro Horie

Stuart Mark Pomerantz

Joanna M Newman

Jean-Michel Berthoud

Eric S Beale

Nathalie Castel

Marc Robins

Andy Harding

Joe Weil

Xiaojin Shi

Marco Zuliani

Francesco Rossi

Bartlomiej W Rymkowski

Alexey Marinichev

Benjamin Poulain

Robert M Chinn

The present disclosure generally relates to displaying visual effects in image data. In some examples, visual effects include an avatar displayed on a user's face. In some examples, visual effects include stickers applied to image data. In some examples, visual effects include screen effects. In some examples, visual effects are modified based on depth data in the image data.

Creative camera

Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or 'AR selfies.' In an embodiment, a method comprises: capturing, by a first camera of a mobile device, live image data, the live image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Augmented reality self-portraits

Artistic styles extracted from one or more source images may be applied to one or more target images, e.g., in the form of stylized images and/or stylized video sequences. The extracted artistic style may be stored as a plurality of layers in a neural network, which neural network may be further optimized, e.g., via the fusion of various elements of the network's architectures. An optimized network architecture may be determined for each processing environment in which the network will be applied. The artistic style may be applied to the obtained images and/or video sequence of images using various optimization methods, such as the use of scalars to control the resolution of the unstylized and stylized images, temporal consistency constraints, as well as the use of dynamically adjustable or selectable versions of Deep Neural Networks (DNN) that are responsive to system performance parameters, such as available processing resources and thermal capacity.

Flexible resolution support for image and video style transfer

Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or 'AR selfies.' In an embodiment, a method comprises: capturing, by a first camera of a mobile device, image data, the image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Creating augmented reality self-portraits using machine learning

A user can control the animation of an object via an interface that includes a control area and a user-manipulable control element. The control area includes an ellipse. The user-manipulable control element includes a three-dimensional arrow with a straight body, a three-dimensional arrow with a curved body, or a sphere. In one embodiment, the interface includes a virtual trackball that is used to manipulate the user-manipulable control element.

User interface for controlling three-dimensional animation of an object

Growing community of inventors

Los Angeles, CA, United States of America

Brian Edward Walsh