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公开(公告)号：US20180122053A1
公开(公告)日：2018-05-03
申请号：US15342041
申请日：2016-11-02
Applicant: Adobe Systems Incorporated
Inventor： Scott D. Cohen , Brian L. Price
CPC classification number: G06T7/90 , G06T11/001 , G06T2207/10024
Abstract: Techniques and systems are described to recolor a group of images for color consistency. Techniques include extracting color palettes for images of the group of images and generating a group theme color palette based on the color palettes for the images. Image color palettes are then mapped to the group theme color palette and the images are modified in response to the mapping. In some examples, the mapping includes discouraging multiple colors of a single color palette from mapping to a single color of the group theme color palette. Additionally, or alternatively, the mapping includes discouraging a forced mapping of a dissimilar color of an image color palette from mapping to the group theme color palette.
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公开(公告)号：US20170220230A1
公开(公告)日：2017-08-03
申请号：US15014765
申请日：2016-02-03
Applicant: Adobe Systems Incorporated
Inventor： Brian L. Price , Scott D. Cohen , Jie Feng
IPC: G06F3/0484 , G06T11/60
CPC classification number: G06F3/04845 , G06T7/10 , G06T7/11 , G06T7/143 , G06T7/194 , G06T7/215 , G06T11/001 , G06T11/60 , G06T2200/24
Abstract: User input-based object selection using multiple visual cues is described. User selection input is received for selecting a portion of an image. Once the user selection input is received, one of a plurality of visual cues that convey different information about content depicted in the image is selected for each pixel. The one visual cue is selected as a basis for identifying the pixel as part of the selected portion of the image or part of an unselected remainder of the image. The visual cues are selected by determining confidences, based in part on the user selection input, that the plurality of visual cues can be used to discriminate whether the pixel is part of the selected portion or part of the remainder. The information conveyed by the selected visual cues is used to identify the pixels as part of the selected portion or part of the remainder.
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公开(公告)号：US20170132498A1
公开(公告)日：2017-05-11
申请号：US14978421
申请日：2015-12-22
Applicant: Adobe Systems Incorporated
Inventor： Scott D. Cohen , Walter Wei-Tuh Chang , Brian L. Price , Mohamed Hamdy Mahmoud Abdelbaky Elhoseiny
CPC classification number: G06F17/2785 , G06K9/4685 , G06K9/6232 , G06N3/0427 , G06N3/0445 , G06N3/0454 , G06N3/08 , G06N5/022
Abstract: Techniques and systems are described to model and extract knowledge from images. A digital medium environment is configured to learn and use a model to compute a descriptive summarization of an input image automatically and without user intervention. Training data is obtained to train a model using machine learning in order to generate a structured image representation that serves as the descriptive summarization of an input image. The images and associated text are processed to extract structured semantic knowledge from the text, which is then associated with the images. The structured semantic knowledge is processed along with corresponding images to train a model using machine learning such that the model describes a relationship between text features within the structured semantic knowledge. Once the model is learned, the model is usable to process input images to generate a structured image representation of the image.
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公开(公告)号：US20170075544A1
公开(公告)日：2017-03-16
申请号：US14853069
申请日：2015-09-14
Applicant: Adobe Systems Incorporated
Inventor： Brian L. Price , Ian D. Sachs
IPC: G06F3/0484 , G06T7/00
CPC classification number: G06F3/04845 , G06F3/04842 , G06T7/10 , G06T7/11 , G06T7/13 , G06T7/143 , G06T2207/10024 , G06T2207/20076 , G06T2207/20096
Abstract: Probabilistic determination of selected image portions is described. In one or more implementations, a selection input is received for selecting a portion of an image. For pixels of the image that correspond to the selection input, probabilities are determined that the pixels are intended to be included as part of a selected portion of the image. In particular, the probability that a given pixel is intended to be included as part of the selected portion of the image is determined as a function of position relative to center pixels of the selection input as well as a difference in one or more visual characteristics with the center pixels. The determined probabilities can then be used to segment the selected portion of the image from a remainder of the image. Based on the segmentation of the selected portion from the remainder of the image, selected portion data can be generated that defines the selected portion of the image
Abstract translation: 描述所选图像部分的概率确定。 在一个或多个实现中，接收用于选择图像的一部分的选择输入。 对于对应于选择输入的图像的像素，确定概率是将像素包括为图像的选定部分的一部分。 特别地，将给定像素旨在作为图像的所选部分的一部分包括的概率被确定为相对于选择输入的中心像素的位置的函数，以及一个或多个视觉特征与第 中心像素。 然后可以使用所确定的概率来从图像的其余部分中分割图像的所选部分。 基于来自图像的其余部分的所选部分的分割，可以生成定义图像的所选部分的所选部分数据
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公开(公告)号：US20160350930A1
公开(公告)日：2016-12-01
申请号：US14724660
申请日：2015-05-28
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Scott D. Cohen , Peng Wang , Xiaohui Shen , Brian L. Price
CPC classification number: G06K9/66 , G06K9/00664 , G06K9/4628 , G06K9/6272 , G06T7/50 , G06T2207/20081
Abstract: Joint depth estimation and semantic labeling techniques usable for processing of a single image are described. In one or more implementations, global semantic and depth layouts are estimated of a scene of the image through machine learning by the one or more computing devices. Local semantic and depth layouts are also estimated for respective ones of a plurality of segments of the scene of the image through machine learning by the one or more computing devices. The estimated global semantic and depth layouts are merged with the local semantic and depth layouts by the one or more computing devices to semantically label and assign a depth value to individual pixels in the image.
Abstract translation: 描述了可用于处理单个图像的联合深度估计和语义标注技术。 在一个或多个实现中，通过一个或多个计算设备的机器学习来估计图像的场景的全局语义和深度布局。 还通过一个或多个计算设备的机器学习来估计图像场景的多个片段中的各个片段的局部语义和深度布局。 估计的全局语义和深度布局由一个或多个计算设备与本地语义和深度布局合并，以语义地标记并分配图像中的各个像素的深度值。
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Patent Agency Ranking
公开(公告)号：US09454712B2
公开(公告)日：2016-09-27
申请号：US14510000
申请日：2014-10-08
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Xiaohui Shen , Brian L. Price , Jianming Zhang
CPC classification number: G06K9/4671 , G06T11/60
Abstract: Saliency map computation is described. In one or more implementations, a base saliency map is generated for an image of a scene. The base saliency map may be generated from intermediate saliency maps computed for boundary regions of the image. Each of the intermediate saliency maps may represent visual saliency of portions of the scene that are captured in the corresponding boundary region. The boundary regions may include, for instance, a top boundary region, a bottom boundary region, a left boundary region, and a right boundary region. Further, the intermediate saliency maps may be combined in such a way that an effect of a foreground object on the saliency map is suppressed. The foreground objects for which the effect is suppressed are those that occupy a majority of one of the boundary regions.
Abstract translation: 描述了显着地图计算。 在一个或多个实现中，为场景的图像生成基本显着图。 可以从为图像的边界区域计算的中间显着图生成基本显着图。 每个中间显着图可以表示在相应边界区域中捕获的场景的部分的视觉显着性。 边界区域可以包括例如顶边界区域，底边界区域，左边界区域和右边界区域。 此外，中间显着图可以以这样的方式组合，即前景对象对显着图的影响被抑制。 效果被抑制的前景对象是占据边界区域中的大多数的那些。
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公开(公告)号：US20160062615A1
公开(公告)日：2016-03-03
申请号：US14469910
申请日：2014-08-27
Applicant: Adobe Systems Incorporated
Inventor： Brian L. Price , Byungmoon Kim
IPC: G06F3/0484 , G06F3/0482
Abstract: Combined selection tool techniques are described in which selection of portions within an image is enabled via a tool configured to selectively switch between a coarse selection mode and a refinement selection mode. In one or more implementations, an image is exposed for editing in a user interface and input is obtained to select portions of the image using the tool. The selection mode is automatically toggled between the coarse selection mode and refinement selection mode based on characteristics of the input, such as position and velocity of the input or gestures mapped to the input. Then, selection boundaries defining the selection of portions of the image are modified in accordance with the input. In one approach, the coarse selection mode corresponds to a graph cut mechanism and the refinement selection mode corresponds to a level set mechanism.
Abstract translation: 描述了组合的选择工具技术，其中通过经配置以选择在粗选择模式和细化选择模式之间切换的工具启用图像内的部分的选择。 在一个或多个实现中，图像被曝光以在用户界面中进行编辑，并且获得输入以使用该工具来选择图像的部分。 选择模式根据输入的特征，例如输入的位置和速度或映射到输入的手势，在粗略选择模式和细化选择模式之间自动切换。 然后，根据输入修改定义图像部分选择的选择边界。 在一种方法中，粗选择模式对应于图切割机制，并且细化选择模式对应于级别设置机制。
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公开(公告)号：US09135710B2
公开(公告)日：2015-09-15
申请号：US13690755
申请日：2012-11-30
Applicant: Adobe Systems Incorporated
Inventor： Scott D. Cohen , Brian L. Price , Gowri Somanath
CPC classification number: G06T7/0075 , G01S17/023 , G01S17/89 , G06T7/593 , G06T2207/20212
Abstract: Depth map stereo correspondence techniques are described. In one or more implementations, a depth map generated through use of a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. For example, the depth map may be utilized to describe depth of an image scene which may be used as part of a stereo correspondence calculation. The depth map may also be utilized as part of a determination of a search range to be employed as part of the stereo correspondence calculation.
Abstract translation: 描述了深度图立体声对应技术。 在一个或多个实现中，通过使用深度传感器生成的深度图被用作立体图像的处理的一部分，以帮助识别立体图像的哪些部分彼此对应。 例如，深度图可以用于描述可以用作立体声对应计算的一部分的图像场景的深度。 深度图也可以用作确定要用作立体声对应计算的一部分的搜索范围的一部分。
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公开(公告)号：US09064318B2
公开(公告)日：2015-06-23
申请号：US13660159
申请日：2012-10-25
Applicant: Adobe Systems Incorporated
Inventor： Brian L. Price , Scott D. Cohen , Jacqueline L. Feild , Gavin Stuart Peter Miller
CPC classification number: G06T7/0081 , G06T7/11 , G06T7/194 , G06T2207/10024
Abstract: Image matting and alpha value techniques are described. In one or more implementations, techniques are described in which matting operations are applied to image data that is in a raw or substantially raw image format. This may be used to decompose image data into foreground and background images as well as to generate an alpha value that describes a linear combination of the foreground and background images for a respective pixel. Further, implementations are also described in which a plurality of alpha values is generated for each of a plurality of pixels. These alpha values may be utilized to support a variety of different functionality, such as matting operations and so on.
Abstract translation: 描述了图像消光和α值技术。 在一个或多个实现中，描述了将消光操作应用于处于原始或基本上原始图像格式的图像数据的技术。 这可以用于将图像数据分解成前景和背景图像，以及生成描述相应像素的前景和背景图像的线性组合的α值。 此外，还描述了为多个像素中的每一个生成多个α值的实现。 这些α值可用于支持各种不同的功能，例如消光操作等等。
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40.发明授权公开(公告)号：US08873835B2
公开(公告)日：2014-10-28
申请号：US13675905
申请日：2012-11-13
Applicant: Adobe Systems Incorporated
Inventor： Paul Asente , Scott D. Cohen , Brian L. Price , Lesley Ann Northam
CPC classification number: G06K9/46 , G06K9/00208 , G06K9/342 , G06K9/6284 , G06T7/11 , G06T7/174 , G06T2207/10012
Abstract: Methods and apparatus for disparity map correction through statistical analysis on local neighborhoods. A disparity map correction technique may be used to correct mistakes in a disparity or depth map. The disparity map correction technique may detect and mark invalid pixel pairs in a disparity map, segment the image, and perform a statistical analysis of the disparities in each segment to identify outliers. The invalid and outlier pixels may then be corrected using other disparity values in the local neighborhood. Multiple iterations of the disparity map correction technique may be performed to further improve the output disparity map.
Abstract translation: 通过对当地社区进行统计分析的视差图校正方法和装置。 视差图校正技术可用于纠正视差或深度图中的错误。 视差图校正技术可以检测和标记视差图中的无效像素对，对图像进行分段，并对每个段中的差异进行统计分析以识别异常值。 然后可以使用本地邻域中的其他视差值来校正无效和异常值像素。 可以执行视差图校正技术的多次迭代以进一步改善输出视差图。
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