Direct thin boundary prediction
    31.
    发明授权

    公开(公告)号:US10977798B2

    公开(公告)日:2021-04-13

    申请号:US16545158

    申请日:2019-08-20

    Applicant: Apple Inc.

    Abstract: In some implementations a neural network is trained to perform to directly predict thin boundaries of objects in images based on image characteristics. A neural network can be trained to predict thin boundaries of objects without requiring subsequent computations to reduce the thickness of the boundary prediction. Instead, the network is trained to make the predicted boundaries thin by effectively suppressing non-maximum values in normal directions along what might otherwise be a thick predicted boundary. To do so, the neural network can be trained to determine normal directions and suppress non-maximum values based on those determined normal directions.

    Object Relationship Estimation From A 3D Semantic Mesh

    公开(公告)号:US20210073429A1

    公开(公告)日:2021-03-11

    申请号:US16984406

    申请日:2020-08-04

    Applicant: Apple Inc.

    Abstract: Implementations disclosed herein provide systems and methods that determine relationships between objects based on an original semantic mesh of vertices and faces that represent the 3D geometry of a physical environment. Such an original semantic mesh may be generated and used to provide input to a machine learning model that estimates relationships between the objects in the physical environment. For example, the machine learning model may output a graph of nodes and edges indicating that a vase is on top of a table or that a particular instance of a vase, V1, is on top of a particular instance of a table, T1.

    Attention diversion control
    33.
    发明授权

    公开(公告)号:US10891922B1

    公开(公告)日:2021-01-12

    申请号:US16508467

    申请日:2019-07-11

    Applicant: Apple Inc.

    Abstract: In one implementation, a method is disclosed for controlling attention diversions while presenting computer-generated reality (CGR) environments on an electronic device. The method includes presenting content representing a view of CGR environment on a display. While presenting the content, an object is detected in a physical environment in which the electronic device is located using an image sensor of the electronic device. The method further includes determining whether the object exhibits a characteristic indicative of attention-seeking behavior. In accordance with a determination that the object exhibits the characteristic, a visual cue corresponding to the object is presented on a first portion of the display without modifying the presentation of the content on a second portion of the display.

    METHOD AND DEVICE FOR GENERATING A SYNTHESIZED REALITY RECONSTRUCTION OF FLAT VIDEO CONTENT

    公开(公告)号:US20240013487A1

    公开(公告)日:2024-01-11

    申请号:US17862301

    申请日:2022-07-11

    Applicant: Apple Inc.

    CPC classification number: G06T19/00 G06V20/41

    Abstract: In one implementation, a method includes: identifying a plurality of plot-effectuators and a plurality of environmental elements within a scene associated with a portion of video content; determining one or more spatial relationships between the plurality of plot-effectuators and the plurality of environmental elements within the scene; synthesizing a representation of the scene based at least in part on the one or more spatial relationships; extracting a plurality of action sequences corresponding to the plurality of plot-effectuators based at least in part on the portion of the video content; and generating a corresponding synthesized reality (SR) reconstruction of the scene by driving a plurality of digital assets, associated with the plurality of plot-effectuators, within the representation of the scene according to the plurality of action sequences.

    METHOD AND DEVICE FOR PRESENTING SYNTHESIZED REALITY COMPANION CONTENT

    公开(公告)号:US20230351644A1

    公开(公告)日:2023-11-02

    申请号:US18215311

    申请日:2023-06-28

    Applicant: Apple Inc.

    CPC classification number: G06T11/00 G06F3/04883

    Abstract: In one implementation, a method includes: obtaining a user input to view SR content associated with video content; if the video content includes a first scene when the user input was detected: obtaining first SR content for a first time period of the video content associated with the first scene; obtaining a task associated with the first scene; and causing presentation of the first SR content and a first indication of the task associated with the first scene; and if the video content includes a second scene when the user input was detected: obtaining second SR content for a second time period of the video content associated with the second scene; obtaining a task associated with the second scene; and causing presentation of the second SR content and a second indication of the task associated with the second scene.

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