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    Utilizing interactive deep learning to select objects in digital visual media
    11.
    发明授权
    Utilizing interactive deep learning to select objects in digital visual media 有权

    公开(公告)号：US10192129B2

    公开(公告)日：2019-01-29

    申请号：US14945245

    申请日：2015-11-18

    Applicant: Adobe Systems Incorporated

    Inventor： Brian Price ,  Scott Cohen ,  Ning Xu

    IPC: G06K9/32 ,  G06K9/46 ,  G06K9/36

    Abstract: Systems and methods are disclosed for selecting target objects within digital images. In particular, in one or more embodiments, the disclosed systems and methods generate a trained neural network based on training digital images and training indicators. Moreover, one or more embodiments of the disclosed systems and methods utilize a trained neural network and iterative user indicators to select targeted objects in digital images. Specifically, the disclosed systems and methods can transform user indicators into distance maps that can be utilized in conjunction with color channels and a trained neural network to identify pixels that reflect the target object.

    Planar region guided 3D geometry estimation from a single image
    12.
    发明授权
    Planar region guided 3D geometry estimation from a single image 有权

    公开(公告)号：US09990728B2

    公开(公告)日：2018-06-05

    申请号：US15261749

    申请日：2016-09-09

    Applicant: ADOBE SYSTEMS INCORPORATED

    Inventor： Xiaohui Shen ,  Scott Cohen ,  Peng Wang ,  Bryan Russell ,  Brian Price ,  Jonathan Eisenmann

    IPC: G06T7/00

    CPC classification number: G06T7/50 ,  G06T7/0051 ,  G06T2207/20084

    Abstract: Techniques for planar region-guided estimates of 3D geometry of objects depicted in a single 2D image. The techniques estimate regions of an image that are part of planar regions (i.e., flat surfaces) and use those planar region estimates to estimate the 3D geometry of the objects in the image. The planar regions and resulting 3D geometry are estimated using only a single 2D image of the objects. Training data from images of other objects is used to train a CNN with a model that is then used to make planar region estimates using a single 2D image. The planar region estimates, in one example, are based on estimates of planarity (surface plane information) and estimates of edges (depth discontinuities and edges between surface planes) that are estimated using models trained using images of other scenes.

    Image segmentation for a live camera feed
    13.
    发明授权
    Image segmentation for a live camera feed 有权

    公开(公告)号：US09774793B2

    公开(公告)日：2017-09-26

    申请号：US14449351

    申请日：2014-08-01

    Applicant: Adobe Systems Incorporated

    Inventor： Brian Price

    IPC: G06K9/34 ,  H04N5/272 ,  H04N5/222 ,  G06T7/11 ,  G06T7/162 ,  G06T7/194

    CPC classification number: H04N5/272 ,  G06T7/11 ,  G06T7/162 ,  G06T7/194 ,  G06T2207/10016 ,  H04N5/2226

    Abstract: Techniques are disclosed for segmenting an image frame of a live camera feed. A biasing scheme can be used to initially localize pixels within the image that are likely to contain the object being segmented. An optimization algorithm for an energy optimization function, such as a graph cut algorithm, can be used with a non-localized neighborhood graph structure and the initial location bias for localizing pixels in the image frame representing the object. Subsequently, a matting algorithm can be used to define a pixel mask surrounding at least a portion of the object boundary. The bias and the pixel mask can be continuously updated and refined as the image frame changes with the live camera feed.

    Image Object Segmentation Using Examples
    15.
    发明申请
    Image Object Segmentation Using Examples 有权
    使用实例的图像对象分割

    公开(公告)号：US20170039723A1

    公开(公告)日：2017-02-09

    申请号：US14817731

    申请日：2015-08-04

    Applicant: Adobe Systems Incorporated

    Inventor： Brian Price ,  Zhe Lin ,  Scott Cohen ,  Jimei Yang

    IPC: G06T7/00 ,  G06K9/62

    CPC classification number: G06T7/251 ,  G06K9/6215 ,  G06T7/11 ,  G06T7/174 ,  G06T2207/10024 ,  G06T2207/20076 ,  G06T2207/20081

    Abstract: Systems and methods are disclosed herein for using one or more computing devices to automatically segment an object in an image by referencing a dataset of already-segmented images. The technique generally involves identifying a patch of an already-segmented image in the dataset based on the patch of the already-segmented image being similar to an area of the image including a patch of the image. The technique further involves identifying a mask of the patch of the already-segmented image, the mask representing a segmentation in the already-segmented image. The technique also involves segmenting the object in the image based on at least a portion of the mask of the patch of the already-segmented image.

    Abstract translation: 本文公开的系统和方法用于使用一个或多个计算设备通过参考已经分割的图像的数据集自动地分割图像中的对象。 该技术通常涉及基于已经分段的图像的片段类似于包括图像的片段的图像的区域来识别数据集中的已经分割的图像的片段。 该技术还涉及识别已经分割的图像的斑块的掩模，该掩码表示已经分割的图像中的分割。 该技术还涉及基于已经分割的图像的补片的掩模的至少一部分来分割图像中的对象。

    Forecasting Multiple Poses Based on a Graphical Image
    18.
    发明申请
    Forecasting Multiple Poses Based on a Graphical Image 审中-公开

    公开(公告)号：US20180293738A1

    公开(公告)日：2018-10-11

    申请号：US15481564

    申请日：2017-04-07

    Applicant: Adobe Systems Incorporated

    Inventor： Jimei Yang ,  Yu-Wei Chao ,  Scott Cohen ,  Brian Price

    IPC: G06T7/246 ,  G06N3/04 ,  G06N5/04

    Abstract: A forecasting neural network receives data and extracts features from the data. A recurrent neural network included in the forecasting neural network provides forecasted features based on the extracted features. In an embodiment, the forecasting neural network receives an image, and features of the image are extracted. The recurrent neural network forecasts features based on the extracted features, and pose is forecasted based on the forecasted features. Additionally or alternatively, additional poses are forecasted based on additional forecasted features.

    PLANAR REGION GUIDED 3D GEOMETRY ESTIMATION FROM A SINGLE IMAGE
    19.
    发明申请
    PLANAR REGION GUIDED 3D GEOMETRY ESTIMATION FROM A SINGLE IMAGE 审中-公开

    公开(公告)号：US20180286061A1

    公开(公告)日：2018-10-04

    申请号：US15996833

    申请日：2018-06-04

    Applicant: Adobe Systems Incorporated

    Inventor： Xiaohui Shen ,  Scott Cohen ,  Peng Wang ,  Bryan Russell ,  Brian Price ,  Jonathan Eisenmann

    IPC: G06T7/50

    CPC classification number: G06T7/50 ,  G06T7/13 ,  G06T7/62 ,  G06T2207/20084

    Abstract: Techniques for planar region-guided estimates of 3D geometry of objects depicted in a single 2D image. The techniques estimate regions of an image that are part of planar regions (i.e., flat surfaces) and use those planar region estimates to estimate the 3D geometry of the objects in the image. The planar regions and resulting 3D geometry are estimated using only a single 2D image of the objects. Training data from images of other objects is used to train a CNN with a model that is then used to make planar region estimates using a single 2D image. The planar region estimates, in one example, are based on estimates of planarity (surface plane information) and estimates of edges (depth discontinuities and edges between surface planes) that are estimated using models trained using images of other scenes.

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