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。

公开(公告)号：US09569684B2

公开(公告)日：2017-02-14

申请号：US14020969

申请日：2013-09-09

Applicant: Adobe Systems Incorporated

Inventor： Jianchao Yang ,  Zhe Lin

IPC: G06T3/40 ,  G06K9/46 ,  G06T5/00 ,  G06K9/62

CPC classification number: G06T5/50 ,  G06K9/46 ,  G06K9/4609 ,  G06K9/4647 ,  G06K9/6259 ,  G06T3/4053 ,  G06T3/4076 ,  G06T5/002 ,  G06T5/003 ,  G06T2207/10024 ,  G06T2207/20192 ,  G06T2207/20216

Abstract: Systems and methods are provided for image enhancement using self-examples in combination with external examples. In one embodiment, an image manipulation application receives an input image patch of an input image. The image manipulation application determines a first weight for an enhancement operation using self-examples and a second weight for an enhancement operation using external examples. The image manipulation application generates a first interim output image patch by applying the enhancement operation using self-examples to the input image patch and a second interim output image patch by applying the enhancement operation using external examples to the input image patch. The image manipulation application generates an output image patch by combining the first and second interim output image patches as modified using the first and second weights.

Abstract translation: 提供了使用自身实例与外部示例组合的图像增强的系统和方法。 在一个实施例中，图像处理应用接收输入图像的输入图像块。 图像处理应用使用自身示例确定用于增强操作的第一权重，并且使用外部示例来确定用于增强操作的第二权重。 图像处理应用程序通过使用自身示例将增强操作应用于输入图像贴片和第二中期输出图像贴图，通过使用外部示例将输入图像贴图应用增强操作来生成第一临时输出图像贴片。 图像处理应用程序通过组合使用第一和第二权重修改的第一和第二临时输出图像块来生成输出图像块。

公开(公告)号：US20160379132A1

公开(公告)日：2016-12-29

申请号：US14748059

申请日：2015-06-23

Applicant: Adobe Systems Incorporated

Inventor： Hailin Jin ,  Chen Fang ,  Jianchao Yang ,  Zhe Lin

IPC: G06N99/00 ,  H04L12/26 ,  H04L29/08

Abstract: The present disclosure is directed to collaborative feature learning using social media data. For example, a machine learning system may identify social media data that includes user behavioral data, which indicates user interactions with content item. Using the identified social user behavioral data, the machine learning system may determine latent representations from the content items. In some embodiments, the machine learning system may train a machine-learning model based on the latent representations. Further, the machine learning system may extract features of the content item from the trained machine-learning model.

Abstract translation: 本公开涉及使用社交媒体数据的协作特征学习。 例如，机器学习系统可以识别包括用户行为数据的社交媒体数据，其指示用户与内容项目的交互。 使用所识别的社会用户行为数据，机器学习系统可以确定来自内容项目的潜在表示。 在一些实施例中，机器学习系统可以基于潜在表示来训练机器学习模型。 此外，机器学习系统可以从训练的机器学习模型中提取内容项的特征。

公开(公告)号：US09471966B2

公开(公告)日：2016-10-18

申请号：US14550808

申请日：2014-11-21

Applicant: Adobe Systems Incorporated

Inventor： Zhe Lin ,  Byungmoon Kim ,  Yuan Gao

IPC: G06K9/40 ,  G06T5/00 ,  G06F3/041

CPC classification number: G06F3/04845 ,  G06F3/041 ,  G06F3/04817 ,  G06F3/04847 ,  G06F3/0488 ,  G06F3/04883 ,  G06T5/001 ,  G06T5/002 ,  G06T5/003 ,  G06T2200/24

Abstract: This document describes techniques and apparatuses for area-dependent image enhancement. These techniques are capable of enabling selection, through a touch-enabled mobile-device display, of an area of a photographic image through movement of a spatially-variable implement, such as brush icon moved over the image. Selected areas can be enhanced differently than other areas, such as to apply sharpening to the selected area and blurring to a non-selected area.

Abstract translation: 本文档描述了区域依赖图像增强的技术和装置。 这些技术能够通过诸如移动在图像上的画笔图标的空间可变的工具的移动，使得能够通过启用触摸的移动设备显示来选择摄影图像的区域。 所选区域可以与其他区域不同地增强，例如对所选择的区域应用锐化和模糊到未选择的区域。

公开(公告)号：US09424484B2

公开(公告)日：2016-08-23

申请号：US14335059

申请日：2014-07-18

Applicant: Adobe Systems Incorporated

Inventor： Xiaohui Shen ,  Zhe Lin ,  Jonathan W. Brandt

IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62 ,  G06F17/30

CPC classification number: G06K9/6256 ,  G06F17/30247 ,  G06F17/30253 ,  G06K9/46 ,  G06K9/4676 ,  G06K9/469 ,  G06N5/04 ,  G06N99/005

Abstract: Feature interpolation techniques are described. In a training stage, features are extracted from a collection of training images and quantized into visual words. Spatial configurations of the visual words in the training images are determined and stored in a spatial configuration database. In an object detection stage, a portion of features of an image are extracted from the image and quantized into visual words. Then, a remaining portion of the features of the image are interpolated using the visual words and the spatial configurations of visual words stored in the spatial configuration database.

Abstract translation: 描述特征插值技术。 在训练阶段，从训练图像的集合中提取特征并量化为视觉词。 训练图像中的视觉词的空间配置被确定并存储在空间配置数据库中。 在物体检测阶段，从图像中提取图像的特征的一部分并量化为视觉词。 然后，使用存储在空间配置数据库中的视觉词和视觉词的空间配置来内插图像的特征的剩余部分。

公开(公告)号：US09330334B2

公开(公告)日：2016-05-03

申请号：US14062559

申请日：2013-10-24

Applicant: Adobe Systems Incorporated

Inventor： Zhe Lin ,  Radomir Mech ,  Peng Wang

IPC: G06K9/46 ,  G06K9/66 ,  G06T7/00

CPC classification number: G06K9/4671 ,  G06T7/11 ,  G06T7/136 ,  G06T7/162 ,  G06T7/194 ,  G06T2207/20004 ,  G06T2207/20016 ,  G06T2207/20076 ,  G06T2207/20081

Abstract: In techniques for iterative saliency map estimation, a salient regions module applies a saliency estimation technique to compute a saliency map of an image that includes image regions. A salient image region of the image is determined from the saliency map, and an image region that corresponds to the salient image region is removed from the image. The salient regions module then iteratively determines subsequent salient image regions of the image utilizing the saliency estimation technique to recompute the saliency map of the image with the image region removed, and removes the image regions that correspond to the subsequent salient image regions from the image. The salient image regions of the image are iteratively determined until no salient image regions are detected in the image, and a salient features map is generated that includes each of the salient image regions determined iteratively and combined to generate the final saliency map.

Abstract translation: 在迭代显着性图估计技术中，显着区域模块应用显着性估计技术来计算包括图像区域的图像的显着性图。 从显着性图确定图像的显着图像区域，并且从图像中去除对应于显着图像区域的图像区域。 显着区域模块然后使用显着性估计技术迭代地确定图像的随后的显着图像区域，以重新计算去除图像区域的图像的显着图，并且从图像中去除与后续显着图像区域相对应的图像区域。 迭代地确定图像的显着图像区域，直到在图像中没有检测到显着的图像区域，并且生成包括迭代地确定并组合的每个显着图像区域以产生最终显着图的显着特征图。

公开(公告)号：US09230192B2

公开(公告)日：2016-01-05

申请号：US14081684

申请日：2013-11-15

Applicant: Adobe Systems Incorporated

Inventor： Hailin Jin ,  Thomas Le Paine ,  Jianchao Yang ,  Zhe Lin ,  Jonathan W. Brandt

IPC: G06K9/52 ,  G06K9/62 ,  G06K9/46

CPC classification number: G06K9/6267 ,  G06K9/46 ,  G06K9/4652

Abstract: Image classification techniques using images with separate grayscale and color channels are described. In one or more implementations, an image classification network includes grayscale filters and color filters which are separate from the grayscale filters. The grayscale filters are configured to extract grayscale features from a grayscale channel of an image, and the color filters are configured to extract color features from a color channel of the image. The extracted grayscale features and color features are used to identify an object in the image, and the image is classified based on the identified object.

Abstract translation: 描述使用具有单独灰度和颜色通道的图像的图像分类技术。 在一个或多个实现中，图像分类网络包括与灰阶滤波器分离的灰度滤波器和滤色器。 灰度滤波器被配置为从图像的灰度级通道提取灰度特征，并且滤色器被配置为从图像的颜色通道中提取颜色特征。 提取的灰度特征和颜色特征用于识别图像中的对象，并且基于识别的对象对图像进行分类。

公开(公告)号：US20150332438A1

公开(公告)日：2015-11-19

申请号：US14280421

申请日：2014-05-16

Applicant: Adobe Systems Incorporated

Inventor： Zhe Lin ,  Jianchao Yang ,  Hailin Jin ,  Xin Lu

IPC: G06T5/00 ,  G06T5/50

CPC classification number: G06T5/005 ,  G06K9/00664 ,  G06K9/6218 ,  G06T5/002 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Patch partition and image processing techniques are described. In one or more implementations, a system includes one or more modules implemented at least partially in hardware. The one or more modules are configured to perform operations including grouping a plurality of patches taken from a plurality of training samples of images into respective ones of a plurality of partitions, calculating an image processing operator for each of the partitions, determining distances between the plurality of partitions that describe image similarity of patches of the plurality of partitions, one to another, and configuring a database to provide the determined distance and the image processing operator to process an image in response to identification of a respective partition that corresponds to a patch taken from the image.

Abstract translation: 描述了补丁分区和图像处理技术。 在一个或多个实现中，系统包括至少部分地以硬件实现的一个或多个模块。 一个或多个模块被配置为执行操作，包括将从多个图像的训练样本获取的多个补丁分组到多个分区中的相应的分区中，为每个分区计算图像处理算子，确定多个分割之间的距离 描述多个分区的图像相似度的分区，并且配置数据库以提供所确定的距离，并且图像处理运算符响应于对应于所采取的补丁的相应分区的标识来处理图像 从图像。

公开(公告)号：US20150213609A1

公开(公告)日：2015-07-30

申请号：US14169073

申请日：2014-01-30

Applicant: Adobe Systems Incorporated

Inventor： Zhe Lin ,  Radomir Mech ,  Xiaohui Shen ,  Chen Fang

IPC: G06T7/00

CPC classification number: G06T7/0081 ,  G06F3/04845 ,  G06T7/00 ,  G06T11/60 ,  G06T2207/10004 ,  G06T2207/20016 ,  G06T2207/20081 ,  G06T2207/20132 ,  G06T2207/30168

Abstract: Image cropping suggestion is described. In one or more implementations, multiple croppings of a scene are scored based on parameters that indicate visual characteristics established for visually pleasing croppings. The parameters may include a parameter that indicates composition quality of a candidate cropping, for example. The parameters may also include a parameter that indicates whether content appearing in the scene is preserved and a parameter that indicates simplicity of a boundary of a candidate cropping. Based on the scores, image croppings may be chosen, e.g., to present the chosen image croppings to a user for selection. To choose the croppings, they may be ranked according to the score and chosen such that consecutively ranked croppings are not chosen. Alternately or in addition, image croppings may be chosen that are visually different according to scores which indicate those croppings have different visual characteristics.

Abstract translation: 描述了图像裁剪建议。 在一个或多个实现中，基于指示为视觉上令人满意的裁剪而建立的视觉特征的参数对场景进行多次裁剪。 参数可以包括例如表示候选裁剪的组合质量的参数。 参数还可以包括指示是否保存出现在场景中的内容的参数以及指示候选裁剪边界的简单性的参数。 基于分数，可以选择图像裁切，例如，将所选择的图像裁切呈现给用户进行选择。 要选择裁剪，可以根据分数进行排序，并选择不选择连续排序的裁剪。 或者或另外，可以根据指示这些裁剪具有不同视觉特征的分数在视觉上不同地选择图像裁切。

公开(公告)号：US20150146973A1

公开(公告)日：2015-05-28

申请号：US14091972

申请日：2013-11-27

Applicant: Adobe Systems Incorporated

Inventor： Jianchao Yang ,  Zhaowen Wang ,  Zhe Lin ,  Jonathan Brandt

IPC: G06K9/62

CPC classification number: G06K9/6269 ,  G06K9/6235

Abstract: A system and method for distributed similarity learning for high-dimensional image features are described. A set of data features is accessed. Subspaces from a space formed by the set of data features are determined using a set of projection matrices. Each subspace has a dimension lower than a dimension of the set of data features. Similarity functions are computed for the subspaces. Each similarity function is based on the dimension of the corresponding subspace. A linear combination of the similarity functions is performed to determine a similarity function for the set of data features.

Abstract translation: 描述了用于高维图像特征的分布式相似性学习的系统和方法。 访问一组数据功能。 使用一组投影矩阵来确定由该组数据特征形成的空间的子空间。 每个子空间的尺寸小于数据特征集合的维度。 为子空间计算相似度函数。 每个相似度函数基于相应子空间的维度。 执行相似度函数的线性组合以确定该组数据特征的相似度函数。