Apple Inc.

Faceshift Ag

Thibaut Weise

Sofien Bouaziz

Brian Amberg

Mark Pauly

Justin D Stoyles

Hao Li

Aurelio Guzmán

Nicolas V Scapel

Hoan K Pham

Guillaume P Barlier

Thomas Goossens

Bruno M Sommer

Alexandre R Moha

Thomas Kiser

Stefan Brugger

Reinhard Knothe

Nina Damasky

Patrick Snape

Alex Mansfield

Michael Kuhn

Stefan Misslinger

Atulit Kumar

Reinhard Klapfer

Sarah Amsellem

A method of animating a digital character according to facial expressions of a user, comprising the steps of, (a) obtaining a 2D image and 3D depth map of the face of the user, (b) determining expression parameters for a user expression model so that a facial expression of the user-specific expression model represents the face of the user shown in the 2D image and 3D depth map (c) using the expression parameters and an animation prior to determine animation parameters usable to animate a digital character, wherein the animation prior is a sequence of animation parameters which represent predefined animations of a digital character (d) using the animation parameters to animate a digital character so that the digital character mimics the face of the user.

Method for facial animation

Systems and methods for generating a video of an emoji that has been puppeted using inputs from image, depth, and audio. The inputs can capture facial expressions of a user, eye, eyebrow, mouth, and head movements. A pose, held by the user, can be detected that can be used to generate supplemental animation. The emoji can further be animated using physical properties associated with the emoji and captured movements. An emoji of a dog can have its ears move in response to an up-and-down movement, or a shaking of the head. The video can be sent in a message to one or more recipients. A sending device can render the puppeted video in accordance with hardware and software capabilities of a recipient's computer device.

Animated representation of facial expression

A three-dimensional model (e.g., motion capture model) of a user is generated from captured images or captured video of the user. A machine learning network may track poses and expressions of the user to generate and refine the three-dimensional model. Refinement of the three-dimensional model may provide more accurate tracking of the user's face. Refining of the three-dimensional model may include refining the determinations of poses and expressions at defined locations (e.g., eye corners and/or nose) in the three-dimensional model. The refining may occur in an iterative process. Tracking of the three-dimensional model over time (e.g., during video capture) may be used to generate an animated three-dimensional model (e.g., an animated puppet) of the user that simulates the user's poses and expressions.

Generating animated three-dimensional models from captured images

In one implementation, a method includes: determining an interpupillary distance (IPD) measurement for a user based on a function of depth data obtained by the depth sensor and image data obtained by the image sensor; and calibrating a head-mounted device (HMD) provided to deliver augmented reality/virtual reality (AR/VR) content by setting one or more presentation parameters of the HMD based on the IPD measurement in order to tailor one or more AR/VR displays of the HMD to a field-of-view of the user.

Method and device for improved interpupillary distance measurement

Techniques are disclosed for creating avatars from image data of a person. According to these techniques, spatial facial attributes of a subject may be measured from an image representing the subject. The measured facial attributes may be matching to a three-dimensional avatar template. Other attributes of the subject may be identified, such as hair type, hair color, eye color, skin color and the like. For hair type, hair may be generated for the avatar by measuring spatial locations of hair of the subject and the measured hair locations may be compared to locations of hair represented by a plurality of hair templates. A matching hair template may be selected from the plurality of hair templates, which may be used in generating the avatar. An avatar may be generated from the matching avatar template, which may be deformed according to the measured spatial facial attributes, and from the other attributes.

Technique for creating avatar from image data

Emojicon puppeting

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Menlo Park, CA, United States of America

Thibaut Weise