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    Intuitive editing of three-dimensional models
    11.
    发明授权
    Intuitive editing of three-dimensional models 有权

    公开(公告)号：US10957117B2

    公开(公告)日：2021-03-23

    申请号：US16204980

    申请日：2018-11-29

    Applicant: ADOBE INC.

    Inventor： Duygu Ceylan Aksit ,  Vladimir Kim ,  Siddhartha Chaudhuri ,  Radomir Mech ,  Noam Aigerman ,  Kevin Wampler ,  Jonathan Eisenmann ,  Giorgio Gori ,  Emiliano Gambaretto

    IPC: G06T15/00 ,  G06T19/20 ,  G06F3/0481 ,  G06F3/0484

    Abstract: Embodiments of the present invention are directed towards intuitive editing of three-dimensional models. In embodiments, salient geometric features associated with a three-dimensional model defining an object are identified. Thereafter, feature attributes associated with the salient geometric features are identified. A feature set including a plurality of salient geometric features related to one another is generated based on the determined feature attributes (e.g., properties, relationships, distances). An editing handle can then be generated and displayed for the feature set enabling each of the salient geometric features within the feature set to be edited in accordance with a manipulation of the editing handle. The editing handle can be displayed in association with one of the salient geometric features of the feature set.

    Generating smooth animation sequences
    15.
    发明授权
    Generating smooth animation sequences 有权

    公开(公告)号：US10565768B2

    公开(公告)日：2020-02-18

    申请号：US16025767

    申请日：2018-07-02

    Applicant: Adobe Inc.

    Inventor： Stefano Corazza ,  Emiliano Gambaretto

    IPC: G06T13/00 ,  G06T13/40

    Abstract: Systems and methods for generating recommendations for animations to apply to animate 3D characters in accordance with embodiments of the invention are disclosed. One embodiment includes an animation server and a database containing metadata describing a plurality of animations and the compatibility of ordered pairs of the described animations. In addition, the animation server is configured to receive requests for animation recommendations identifying a first animation, generate a recommendation of at least one animation described in the database based upon the first animation, receive a selection of an animation described in the database, and concatenate at least the first animation and the selected animation.

    NEURAL NETWORK-BASED CAMERA CALIBRATION
    16.
    发明申请
    NEURAL NETWORK-BASED CAMERA CALIBRATION 审中-公开

    公开(公告)号：US20190164312A1

    公开(公告)日：2019-05-30

    申请号：US15826331

    申请日：2017-11-29

    Applicant: ADOBE INC.

    Inventor： Kalyan K. Sunkavalli ,  Yannick Hold-Geoffroy ,  Sunil Hadap ,  Matthew David Fisher ,  Jonathan Eisenmann ,  Emiliano Gambaretto

    IPC: G06T7/80 ,  G06T7/00 ,  G06N3/08

    CPC classification number: G06T7/80 ,  G06N3/0454 ,  G06N3/08 ,  G06T7/97 ,  G06T2207/20081 ,  G06T2207/20084

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to generating training image data for a convolutional neural network, encoding parameters into a convolutional neural network, and employing a convolutional neural network that estimates camera calibration parameters of a camera responsible for capturing a given digital image. A plurality of different digital images can be extracted from a single panoramic image given a range of camera calibration parameters that correspond to a determined range of plausible camera calibration parameters. With each digital image in the plurality of extracted different digital images having a corresponding set of known camera calibration parameters, the digital images can be provided to the convolutional neural network to establish high-confidence correlations between detectable characteristics of a digital image and its corresponding set of camera calibration parameters. Once trained, the convolutional neural network can receive a new digital image, and based on detected image characteristics thereof, estimate a corresponding set of camera calibration parameters with a calculated level of confidence.

    Neural network-based camera calibration
    19.
    发明授权
    Neural network-based camera calibration 有权

    公开(公告)号：US10964060B2

    公开(公告)日：2021-03-30

    申请号：US16675641

    申请日：2019-11-06

    Applicant: ADOBE INC.

    Inventor： Kalyan K. Sunkavalli ,  Yannick Hold-Geoffroy ,  Sunil Hadap ,  Matthew David Fisher ,  Jonathan Eisenmann ,  Emiliano Gambaretto

    IPC: G06T7/80 ,  G06N3/08 ,  G06T7/00 ,  G06N3/04

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to generating training image data for a convolutional neural network, encoding parameters into a convolutional neural network, and employing a convolutional neural network that estimates camera calibration parameters of a camera responsible for capturing a given digital image. A plurality of different digital images can be extracted from a single panoramic image given a range of camera calibration parameters that correspond to a determined range of plausible camera calibration parameters. With each digital image in the plurality of extracted different digital images having a corresponding set of known camera calibration parameters, the digital images can be provided to the convolutional neural network to establish high-confidence correlations between detectable characteristics of a digital image and its corresponding set of camera calibration parameters. Once trained, the convolutional neural network can receive a new digital image, and based on detected image characteristics thereof, estimate a corresponding set of camera calibration parameters with a calculated level of confidence.

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