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    Identifying and modifying cast shadows in an image
    1.
    发明授权
    Identifying and modifying cast shadows in an image 有权
    识别和修改图像中的投射阴影

    公开(公告)号：US09430715B1

    公开(公告)日：2016-08-30

    申请号：US14702588

    申请日：2015-05-01

    Applicant: Adobe Systems Incorporated

    Inventor： Jue Wang ,  Kalyan Sunkavalli ,  Li-Qian Ma ,  Elya Shechtman

    IPC: G06K9/34 ,  G06K9/46 ,  G06T5/00 ,  G06K9/42 ,  G06T7/00 ,  G06K9/40 ,  G06K9/44 ,  G06K9/62 ,  G06K9/66

    CPC classification number: G06T7/0081 ,  G06K9/346 ,  G06T5/008 ,  G06T7/11 ,  G06T7/143 ,  G06T2207/10024 ,  G06T2207/20021 ,  G06T2207/20076 ,  G06T2207/20081

    Abstract: Methods and systems for detection and removal of cast shadows from an image. In particular, one or more embodiments compute correspondences between image patches in the image using a grid-based patch-matching algorithm. One or more embodiments then train a regression model to detect shadows from the computed patch correspondences. One or more embodiments then segment the detected shadows into shadow regions and identify cast shadows from the shadow regions. Once the cast shadows are identified, one or more embodiments use patch-based synthesis of pixels guided by a direct inversion of the image. Optionally, one or more methods can use pixels from the synthesized image and the naïve inversion of the image, based on a synthesis confidence of each pixel, to produce a combined result.

    Abstract translation: 用于从图像中检测和删除投影的方法和系统。 特别地，一个或多个实施例使用基于网格的补丁匹配算法来计算图像中的图像斑块之间的对应关系。 然后一个或多个实施例训练回归模型以从计算的补片对应度检测阴影。 然后，一个或多个实施例将检测到的阴影分割成阴影区域，并从阴影区域识别投射阴影。 一旦确定了投影，一个或多个实施例使用基于图像的直接反转引导的基于片段的合成像素。 可选地，一个或多个方法可以基于每个像素的合成置信度使用来自合成图像的像素和图像的初始反转，以产生组合结果。

    Automatically selecting example stylized images for image stylization operations based on semantic content
    2.
    发明授权
    Automatically selecting example stylized images for image stylization operations based on semantic content 有权
    自动选择基于语义内容的图像样式化操作的示例风格化图像

    公开(公告)号：US09594977B2

    公开(公告)日：2017-03-14

    申请号：US14735822

    申请日：2015-06-10

    Applicant: Adobe Systems Incorporated

    Inventor： Zhe Lin ,  Xiaohui Shen ,  Kalyan Sunkavalli ,  Joon-Young Lee

    IPC: G06K9/62 ,  G09G5/00 ,  G06K9/46 ,  G06T7/40 ,  G06K9/52 ,  G06T7/60

    CPC classification number: G06T7/60 ,  G06K9/00624 ,  G06T7/90 ,  G06T11/001

    Abstract: Systems and methods are provided for content-based selection of style examples used in image stylization operations. For example, training images can be used to identify example stylized images that will generate high-quality stylized images when stylizing input images having certain types of semantic content. In one example, a processing device determines which example stylized images are more suitable for use with certain types of semantic content represented by training images. In response to receiving or otherwise accessing an input image, the processing device analyzes the semantic content of the input image, matches the input image to at least one training image with similar semantic content, and selects at least one example stylized image that has been previously matched to one or more training images having that type of semantic content. The processing device modifies color or contrast information for the input image using the selected example stylized image.

    Abstract translation: 提供了系统和方法用于基于内容的图像样式化操作中使用的样式示例的选择。 例如，训练图像可用于识别示例风格化图像，其将在对具有某些类型的语义内容的输入图像进行风格化时生成高质量的程式化图像。 在一个示例中，处理设备确定哪个示例风格化图像更适合于使用由训练图像表示的某些类型的语义内容。 响应于接收或以其他方式访问输入图像，处理设备分析输入图像的语义内容，将输入图像与具有相似语义内容的至少一个训练图像匹配，并且选择至少一个先前已经具有的示例风格化图像 与具有该类型的语义内容的一个或多个训练图像匹配。 处理装置使用所选择的示例风格化图像修改输入图像的颜色或对比度信息。

    Texture Modeling of Image Data
    3.
    发明申请
    Texture Modeling of Image Data 审中-公开
    图像数据的纹理建模

    公开(公告)号：US20150145862A1

    公开(公告)日：2015-05-28

    申请号：US14092210

    申请日：2013-11-27

    Applicant: Adobe Systems Incorporated

    Inventor： Siying Liu ,  Kalyan Sunkavalli ,  Nathan A. Carr ,  Elya Shechtman

    IPC: G06T15/04 ,  G06T19/20 ,  G06T17/20

    CPC classification number: G06T11/001 ,  G06K9/52 ,  G06K9/6211 ,  G06T7/49

    Abstract: Texture modeling techniques for image data are described. In one or more implementations, texels in image data are discovered by one or more computing devices, each texel representing an element that repeats to form a texture pattern in the image data. Regularity of the texels in the image data is modeled by the one or more computing devices to define translations and at least one other transformation of texels in relation to each other.

    Abstract translation: 描述图像数据的纹理建模技术。 在一个或多个实现中，图像数据中的纹理元素由一个或多个计算设备发现，每个纹素表示在图像数据中重复形成纹理图案的元素。 图像数据中的纹理的规则性由一个或多个计算设备建模，以定义相对于彼此的翻译和纹素的至少一个其他变换。

    AUTOMATIC GEOMETRY AND LIGHTING INFERENCE FOR REALISTIC IMAGE EDITING
    4.
    发明申请
    AUTOMATIC GEOMETRY AND LIGHTING INFERENCE FOR REALISTIC IMAGE EDITING 有权
    用于现实图像编辑的自动几何和照明

    公开(公告)号：US20150043806A1

    公开(公告)日：2015-02-12

    申请号：US13962604

    申请日：2013-08-08

    Applicant: Adobe Systems Incorporated

    Inventor： Kevin Karsch ,  Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Hailin Jin

    IPC: G06T7/00

    CPC classification number: G06T15/506 ,  G06T7/536 ,  G06T11/60 ,  G06T15/50 ,  G06T19/20 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2219/2021

    Abstract: Image editing techniques are disclosed that support a number of physically-based image editing tasks, including object insertion and relighting. The techniques can be implemented, for example in an image editing application that is executable on a computing system. In one such embodiment, the editing application is configured to compute a scene from a single image, by automatically estimating dense depth and diffuse reflectance, which respectively form the geometry and surface materials of the scene. Sources of illumination are then inferred, conditioned on the estimated scene geometry and surface materials and without any user input, to form a complete 3D physical scene model corresponding to the image. The scene model may include estimates of the geometry, illumination, and material properties represented in the scene, and various camera parameters. Using this scene model, objects can be readily inserted and composited into the input image with realistic lighting, shadowing, and perspective.

    Abstract translation: 公开了支持许多基于物理的图像编辑任务的图像编辑技术，包括对象插入和重新点亮。 这些技术可以被实现，例如在可在计算系统上执行的图像编辑应用中。 在一个这样的实施例中，编辑应用被配置为通过自动估计分别形成场景的几何和表面材料的密集深度和漫反射度来从单个图像计算场景。 然后推断照明源，根据估计的场景几何和表面材料进行调节，而无需任何用户输入，以形成对应于图像的完整3D物理场景模型。 场景模型可以包括在场景中表示的几何，照明和材料属性以及各种相机参数的估计。 使用这个场景模型，可以使用逼真的照明，阴影和透视，将对象轻松插入并合成到输入图像中。

    CREATING BUMP AND NORMAL MAPS FROM IMAGES WITH MULTI-SCALE CONTROL
    8.
    发明申请
    CREATING BUMP AND NORMAL MAPS FROM IMAGES WITH MULTI-SCALE CONTROL 有权

    公开(公告)号：US20170148205A1

    公开(公告)日：2017-05-25

    申请号：US14946193

    申请日：2015-11-19

    Applicant: Adobe Systems Incorporated

    Inventor： Kalyan Sunkavalli

    IPC: G06T15/04 ,  G06T5/20 ,  G06T5/00 ,  G06T3/40 ,  G06T15/80

    CPC classification number: G06T15/04 ,  G06T2200/24 ,  G06T2210/36

    Abstract: This disclosure relates to generating a bump map and/or a normal map from an image. For example, a method for generating a bump map includes receiving a texture image and a plurality of user-specified weights. The method further includes deriving a plurality of images from the texture image, the plurality of images vary from one another with respect to resolution or sharpness. The method further includes weighting individual images of the plurality of images according to the user-specified weights. The method further includes generating a bump map using the weighted individual images. The method further includes providing an image for display with texture added to a surface of an object in the image based on the bump map.

    Automatic geometry and lighting inference for realistic image editing
    9.
    发明授权
    Automatic geometry and lighting inference for realistic image editing 有权
    自动几何和照明推理，用于逼真的图像编辑

    公开(公告)号：US09299188B2

    公开(公告)日：2016-03-29

    申请号：US13962604

    申请日：2013-08-08

    Applicant: Adobe Systems Incorporated

    Inventor： Kevin Karsch ,  Kalyan Sunkavalli ,  Sunil Hadap ,  Nathan Carr ,  Hailin Jin

    IPC: G06T15/50 ,  G06T7/00 ,  G06T19/20 ,  G06T11/60

    CPC classification number: G06T15/506 ,  G06T7/536 ,  G06T11/60 ,  G06T15/50 ,  G06T19/20 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2219/2021

    Abstract: Image editing techniques are disclosed that support a number of physically-based image editing tasks, including object insertion and relighting. The techniques can be implemented, for example in an image editing application that is executable on a computing system. In one such embodiment, the editing application is configured to compute a scene from a single image, by automatically estimating dense depth and diffuse reflectance, which respectively form the geometry and surface materials of the scene. Sources of illumination are then inferred, conditioned on the estimated scene geometry and surface materials and without any user input, to form a complete 3D physical scene model corresponding to the image. The scene model may include estimates of the geometry, illumination, and material properties represented in the scene, and various camera parameters. Using this scene model, objects can be readily inserted and composited into the input image with realistic lighting, shadowing, and perspective.

    Abstract translation: 公开了支持许多基于物理的图像编辑任务的图像编辑技术，包括对象插入和重新点亮。 这些技术可以被实现，例如在可在计算系统上执行的图像编辑应用中。 在一个这样的实施例中，编辑应用被配置为通过自动估计分别形成场景的几何和表面材料的密集深度和漫反射度来从单个图像计算场景。 然后推断照明源，根据估计的场景几何和表面材料进行调节，而无需任何用户输入，以形成对应于图像的完整3D物理场景模型。 场景模型可以包括在场景中表示的几何，照明和材料属性以及各种相机参数的估计。 使用这个场景模型，可以使用逼真的照明，阴影和透视，将对象轻松插入并合成到输入图像中。

    IMAGE PATCH MATCHING USING PROBABILISTIC SAMPLING BASED ON AN ORACLE
    10.
    发明申请
    IMAGE PATCH MATCHING USING PROBABILISTIC SAMPLING BASED ON AN ORACLE 审中-公开

    公开(公告)号：US20180121754A1

    公开(公告)日：2018-05-03

    申请号：US15342793

    申请日：2016-11-03

    Applicant: Adobe Systems Incorporated

    Inventor： Nathan Carr ,  Kalyan Sunkavalli ,  Michal Lukac ,  Elya Shechtman

    IPC: G06K9/62

    Abstract: The present disclosure is directed toward systems and methods for image patch matching. In particular, the systems and methods described herein sample image patches to identify those image patches that match a target image patch. The systems and methods described herein probabilistically accept image patch proposals as potential matches based on an oracle. The oracle is computationally inexpensive to evaluate but more approximate than similarity heuristics. The systems and methods use the oracle to quickly guide the search to areas of the search space more likely to have a match. Once areas are identified that likely include a match, the systems and methods use a more accurate similarity function to identify patch matches.

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