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公开(公告)号：US12154379B2
公开(公告)日：2024-11-26
申请号：US18306439
申请日：2023-04-25
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
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公开(公告)号：US10223767B2
公开(公告)日：2019-03-05
申请号：US15583465
申请日：2017-05-01
Applicant: Adobe Inc.
Inventor： Byungmoon Kim , Daichi Ito , Gahye Park
Abstract: In embodiments of facial feature liquifying using face mesh, an image processing application is implemented to modify facial features of a face in an image from a combination of deformation fields. The image processing application can generate a face mesh that includes landmark points, and then construct the deformation fields on the face mesh, where the deformation fields are defined by warpable elements formed from the landmark points. The image processing application can also combine the deformation fields. The image processing application can also receive an input to initiate modifying one or more of the facial features of the face in the image using the combined deformation fields.
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公开(公告)号：US20220121841A1
公开(公告)日：2022-04-21
申请号：US17075207
申请日：2020-10-20
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
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公开(公告)号：US10269142B2
公开(公告)日：2019-04-23
申请号：US15336085
申请日：2016-10-27
Applicant: Adobe Inc.
Inventor： Zhili Chen , Daichi Ito , Byungmoon Kim , Gahye Park
Abstract: The present disclosure is directed towards methods and systems for providing a digital mixed output color of two reference colors defined in an RGB model where the digital mixed output color at least generally reflects a color produced by mixing physical pigments of the two reference colors or a custom user-defined color. The systems and methods receive a selection of two reference colors to mix. Additionally, the systems and methods can determine a mixing ratio of the two reference colors. Moreover, the systems and methods query at least one predefined mixing table and identify from the at least one predefined mixing table a mixed output color correlating to a mixture of the two reference colors.
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Patent Agency Ranking
公开(公告)号：US20250069437A1
公开(公告)日：2025-02-27
申请号：US18948067
申请日：2024-11-14
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
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6.发明公开公开(公告)号：US20230260324A1
公开(公告)日：2023-08-17
申请号：US18306439
申请日：2023-04-25
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
CPC classification number: G06V40/174 , G06T7/97 , G06V40/23 , G06F18/22 , G06T2207/20084
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
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公开(公告)号：US11670114B2
公开(公告)日：2023-06-06
申请号：US17075207
申请日：2020-10-20
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
CPC classification number: G06V40/174 , G06K9/6215 , G06T7/97 , G06V40/23 , G06T2207/20084
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
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公开(公告)号：US10755459B2
公开(公告)日：2020-08-25
申请号：US15297938
申请日：2016-10-19
Applicant: Adobe Inc.
Inventor： Zhili Chen , Srinivasa Madhava Phaneendra Angara , Duygu Ceylan Aksit , Byungmoon Kim , Gahye Park
IPC: G06T11/60 , G06F3/0481 , G06T11/00
Abstract: Techniques and systems are described herein that support improved object painting in digital images through use of perspectives and transfers in a digital medium environment. In one example, a user interacts with a two-dimensional digital image in a user interface output by a computing device to apply digital paint. The computing device fits a three-dimensional model to an object within the image, e.g., the face. The object, as fit to the three-dimensional model, is used to support output of a plurality of perspectives of a view of the object with which a user may interact to digitally paint the object. As part of this, digital paint as specified through the user inputs is applied directly by the computing device to a two-dimensional texture map of the object. This may support transfer of digital paint by a computing device between objects by transferring the digital paint using respective two-dimensional texture maps.
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公开(公告)号：US10318128B2
公开(公告)日：2019-06-11
申请号：US14871000
申请日：2015-09-30
Applicant: ADOBE INC.
Inventor： Byungmoon Kim , Gahye Park
IPC: G06F3/048 , G06F3/00 , G06F3/0484 , G06T3/60 , G06T3/40 , G06F3/0488
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for facilitating manipulation of images in response to gestures. A user can provide a gesture to effectuate a desired rotation or scaling of an image region. In some implementations, a user might provide a rotation gesture (i.e., a circular pattern) to cause a rotation of an image region or a stroke gesture (i.e., a straight line pattern) to cause a scaling of an image region. Using intuitive gestures, such as touch gestures, the user can control the direction and magnitude of manipulation to accomplish a desired manipulation (e.g., rotation or scaling) of an image region.
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