-
公开(公告)号：US09251594B2
公开(公告)日：2016-02-02
申请号：US14169025
申请日：2014-01-30
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Xiaohui Shen , Chen Fang
CPC classification number: G06T5/003 , G06F17/30256 , G06F17/3053 , G06T7/00 , G06T11/60 , G06T2207/10004 , G06T2207/10016 , G06T2207/20016 , G06T2207/20092 , G06T2207/20132 , G06T2207/30168 , G06T2210/22
Abstract: Cropping boundary simplicity techniques are described. In one or more implementations, multiple candidate croppings of a scene are generated. For each of the candidate croppings, a score is calculated that is indicative of a boundary simplicity for the candidate cropping. To calculate the boundary simplicity, complexity of the scene along a boundary of a respective candidate cropping is measured. The complexity is measured, for instance, using an average gradient, an image edge map, or entropy along the boundary. Values indicative of the complexity may be derived from the measuring. The candidate croppings may then be ranked according to those values. Based on the scores calculated to indicate the boundary simplicity, one or more of the candidate croppings may be chosen e.g., to present the chosen croppings to a user for selection.
Abstract translation: 描述边界简单技术。 在一个或多个实现中，生成场景的多个候选裁剪。 对于每个候选作物，计算表示候选种植的边界简单性的分数。 为了计算边界简单性，测量沿着相应候选剪切的边界的场景的复杂性。 测量复杂度，例如，使用沿着边界的平均梯度，图像边缘图或熵。 表示复杂性的值可以从测量得出。 然后可以根据这些值对候选作物进行排序。 基于计算的用于指示边界简单性的分数，可以选择一个或多个候选剪切，以将所选择的剪切呈现给用户进行选择。
-
62.发明授权公开(公告)号：US09251569B2
公开(公告)日：2016-02-02
申请号：US14022462
申请日：2013-09-10
Applicant: Adobe Systems Incorporated
Inventor： Chih-Yao Hsieh , Yuyan Song , Zhe Lin
CPC classification number: G06T5/002 , G06T5/20 , G06T7/90 , G06T2207/10024 , G06T2207/20024 , G06T2207/20182
Abstract: Systems and methods herein provide for reduced computations in image processing and a more efficient way of computing distances between patches in patch-based image denoising. One method is operable within a processing system to remove noise from a digital image by generating a plurality of lookup tables of pixel values based on a plurality of comparisons of the digital image to offsets of the digital image, generating integral images from the lookup tables, and computing distances between patches of pixels in the digital image from the integral images. The method also includes computing weights for the patches of pixels in the digital image based on the computed distances and applying the weights to pixels in the digital image on a patch-by-patch basis to restore values of the pixels.
Abstract translation: 这里的系统和方法提供图像处理中的减少的计算以及在基于补丁的图像去噪中计算补片之间的距离的更有效的方式。 一种方法在处理系统内可操作以通过基于数字图像与数字图像的偏移的多个比较生成多个像素值的查找表来从数字图像中去除噪声，从查找表生成整体图像， 以及从整体图像计算数字图像中的像素块之间的距离。 该方法还包括基于所计算的距离计算数字图像中的像素块的权重，并且在逐个补丁的基础上将权重应用于数字图像中的像素以恢复像素的值。
-
公开(公告)号：US20160027181A1
公开(公告)日：2016-01-28
申请号：US14444560
申请日：2014-07-28
Applicant: Adobe Systems Incorporated
Inventor： Xiaohui Shen , Zhe Lin , Jonathan W. Brandt
CPC classification number: G06K9/00268 , G06K9/00228 , G06K9/00281 , G06K9/4676 , G06K9/623 , G06K9/6257
Abstract: Accelerating object detection techniques are described. In one or more implementations, adaptive sampling techniques are used to extract features from an image. Coarse features are extracted from the image and used to generate an object probability map. Then, dense features are extracted from high-probability object regions of the image identified in the object probability map to enable detection of an object in the image. In one or more implementations, cascade object detection techniques are used to detect an object in an image. In a first stage, exemplars in a first subset of exemplars are applied to features extracted from the multiple regions of the image to detect object candidate regions. Then, in one or more validation stages, the object candidate regions are validated by applying exemplars from the first subset of exemplars and one or more additional subsets of exemplars.
Abstract translation: 描述加速对象检测技术。 在一个或多个实现中，使用自适应采样技术来从图像中提取特征。 从图像中提取粗略特征，并用于生成目标概率图。 然后，从在目标概率图中识别的图像的高概率对象区域提取密集特征，以使得能够检测图像中的对象。 在一个或多个实现中，使用级联对象检测技术来检测图像中的对象。 在第一阶段，样本的第一子集中的样本被应用于从图像的多个区域提取的特征以检测对象候选区域。 然后，在一个或多个验证阶段中，通过应用示例的第一子集和示例的一个或多个附加子集来验证对象候选区域。
-
公开(公告)号：US20160027152A1
公开(公告)日：2016-01-28
申请号：US14339874
申请日：2014-07-24
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Chih-Yao Hsieh , Zhe Lin
CPC classification number: G06T5/003 , G06T3/4053 , G06T3/4076 , G06T5/00 , G06T5/001 , G06T5/002 , G06T5/20 , G06T11/00 , G06T11/001 , G06T11/60 , G06T2207/20021 , G06T2207/20024
Abstract: Techniques for enhancing an image using pixel-specific processing. An image can be enhanced by updating selected pixels through patch aggregation. Respective patch values for patches of any size of the image are determined. Patch values provide update information for updating the respective pixels in the patch. Relevant patch values for the selected pixel are identified by identifying associated patches of the pixel. Information from the relevant patch values of the selected pixel may be obtained by averaging the relevant patch values or determining the maximum or minimum patch value. Using this information, pixel-specific processing may be performed to determine an updated pixel value for the selected pixel. Pixel-specific processes may be executed for each of the selected pixels. These pixel-specific processes can be executed in parallel. Therefore, through the execution of pixel-specific processes, which may be performed concurrently, an enhanced image may be determined.
Abstract translation: 使用像素特定处理来增强图像的技术。 通过补丁聚合更新所选像素可以增强图像。 确定任何尺寸图像的补丁的各个补丁值。 补丁值提供更新补丁中各个像素的更新信息。 通过识别像素的相关补丁来识别所选像素的相关补丁值。 可以通过对相关补丁值进行平均或确定最大或最小补丁值来获得来自所选像素的相关补丁值的信息。 使用该信息，可以执行像素特定处理以确定所选择的像素的更新的像素值。 可以针对每个所选择的像素执行像素特定的处理。 这些像素特定的处理可以并行执行。 因此，通过执行可以同时执行的像素特定处理，可以确定增强图像。
-
公开(公告)号：US09245347B2
公开(公告)日：2016-01-26
申请号：US14169073
申请日：2014-01-30
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Xiaohui Shen , Chen Fang
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。
-
Patent Agency Ranking
公开(公告)号：US09208404B2
公开(公告)日：2015-12-08
申请号：US14081489
申请日：2013-11-15
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jonathan W. Brandt , Xiaohui Shen , Haoxiang Li
CPC classification number: G06K9/6269 , G06K9/00234 , G06K9/00288 , G06K9/6257
Abstract: In techniques for object detection with boosted exemplars, weak classifiers of a real-adaboost technique can be learned as exemplars that are collected from example images. The exemplars are examples of an object that is detectable in image patches of an image, such as faces that are detectable in images. The weak classifiers of the real-adaboost technique can be applied to the image patches of the image, and a confidence score is determined for each of the weak classifiers as applied to an image patch of the image. The confidence score of a weak classifier is an indication of whether the object is detected in the image patch of the image based on the weak classifier. All of the confidence scores of the weak classifiers can then be summed to generate an overall object detection score that indicates whether the image patch of the image includes the object.
Abstract translation: 在通过增强的样本进行物体检测的技术中，可以从实例图像中收集真实adaboost技术的弱分类器作为样本。 示例是在图像的图像块中可检测到的对象的示例，例如在图像中可检测的面。 真实adaboost技术的弱分类器可以应用于图像的图像斑块，并且对于每个弱分类器确定应用于图像的图像块的置信度分数。 弱分类器的置信度分数是基于弱分类器在图像的图像块中是否检测到对象的指示。 然后可以将弱分类器的所有置信分数相加以生成指示图像的图像块是否包括对象的整体对象检测分数。
-
公开(公告)号：US09158963B2
公开(公告)日：2015-10-13
申请号：US13645453
申请日：2012-10-04
Applicant: Adobe Systems Incorporated
Inventor： Jonathan W. Brandt , Zhe Lin , Lubomir D. Bourdev , Vuong Le
CPC classification number: G06K9/00281 , G06K9/6209
Abstract: Various embodiments of methods and apparatus for feature point localization are disclosed. An object in an input image may be detected. A profile model may be applied to determine feature point locations for each object component of the detected object. Applying the profile model may include globally optimizing the feature points for each object component to find a global energy minimum. A component-based shape model may be applied to update the respective feature point locations for each object component.
Abstract translation: 公开了用于特征点定位的方法和装置的各种实施例。 可以检测输入图像中的对象。 可以应用轮廓模型来确定检测到的对象的每个对象分量的特征点位置。 应用轮廓模型可以包括全局优化每个对象分量的特征点以找到全局能量最小值。 可以应用基于组件的形状模型来更新每个对象组件的各个特征点位置。
-
公开(公告)号：US09123138B2
公开(公告)日：2015-09-01
申请号：US13920911
申请日：2013-06-18
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jianchao Yang , Scott D. Cohen
CPC classification number: G06T3/40 , G06T3/4076
Abstract: Image upscaling techniques are described. These techniques may include use of iterative and adjustment upscaling techniques to upscale an input image. A variety of functionality may be incorporated as part of these techniques, examples of which include content-adaptive patch finding techniques that may be employed to give preference to an in-place patch to minimize structure distortion. In another example, content metric techniques may be employed to assign weights for combining patches. In a further example, algorithm parameters may be adapted with respect to algorithm iterations, which may be performed to increase efficiency of computing device resource utilization and speed of performance. For instance, algorithm parameters may be adapted to enforce a minimum and/or maximum number to iterations, cease iterations for image sizes over a threshold amount, set sampling step sizes for patches, employ techniques based on color channels (which may include independence and joint processing techniques), and so on.
Abstract translation: 描述了图像升高技术。 这些技术可以包括使用迭代和调整放大技术来升高输入图像。 作为这些技术的一部分，可以并入各种功能，其示例包括可用于优先使用就地补丁以最小化结构失真的内容自适应补片发现技术。 在另一示例中，可以采用内容度量技术来分配用于组合补丁的权重。 在另一示例中，算法参数可以针对算法迭代进行调整，这可以被执行以提高计算设备资源利用率和性能的效率。 例如，算法参数可以适于对迭代执行最小和/或最大数量，停止针对阈值量的图像大小的迭代，设置用于补丁的采样步长，采用基于颜色通道的技术（其可以包括独立性和联合 处理技术）等。
-
公开(公告)号：US20150227817A1
公开(公告)日：2015-08-13
申请号：US14180305
申请日：2014-02-13
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Xiaohui Shen , Chen Fang
CPC classification number: G06K9/6212 , G06K9/00664 , G06K9/4642 , G06K2009/6213
Abstract: In techniques for category histogram image representation, image segments of an input image are generated and bounding boxes are selected that each represent a region of the input image, where each of the bounding boxes include image segments of the input image. A saliency map of the input image can also be generated. A bounding box is applied as a query on an images database to determine database image regions that match the region of the input image represented by the bounding box. The query can be augmented based on saliency detection of the input image region that is represented by the bounding box, and a query result is a ranked list of the database image regions. A category histogram for the region of the input image is then generated based on category labels of each of the database image regions that match the input image region.
Abstract translation: 在类别直方图图像表示的技术中，生成输入图像的图像片段，并且选择每个表示输入图像的区域的边界框，其中每个边界框包括输入图像的图像片段。 也可以生成输入图像的显着图。 将边框应用于图像数据库上的查询，以确定与由边界框表示的输入图像的区域匹配的数据库图像区域。 可以基于由边界框表示的输入图像区域的显着性检测来增加查询，并且查询结果是数据库图像区域的排序列表。 然后基于与输入图像区域匹配的每个数据库图像区域的类别标签来生成输入图像的区域的类别直方图。
-
公开(公告)号：US20150055857A1
公开(公告)日：2015-02-26
申请号：US13970993
申请日：2013-08-20
Applicant: Adobe Systems Incorporated
Inventor： Jue Wang , Zhe Lin , Jianchao Yang , Weilin Huang
IPC: G06K9/18
CPC classification number: G06K9/18 , G06K9/3258
Abstract: A system and method of text detection in an image are described. A component detection module applies a filter having a stroke width constraint and a stroke color constraint to an image to identify text stroke pixels in the image and to generate both a first map based on the stroke width constraint and a second map based on the stroke color constraint. A component filtering module has a first classifier and second classifier. The first classifier is applied to both the first map and the second map to generate a third map identifying a component of a text in the image. The second classifier is applied to the third map to generate a fourth map identifying a text line of the text in the image. A text region locator module thresholds the fourth map to identify text regions in the image.
Abstract translation: 描述图像中文本检测的系统和方法。 分量检测模块将具有笔划宽度约束和笔画颜色约束的滤波器应用于图像以识别图像中的文本笔划像素，并且基于笔画宽度约束生成第一地图，并且基于笔画颜色生成第二地图 约束。 组件过滤模块具有第一分类器和第二分类器。 将第一分类器应用于第一地图和第二地图，以生成标识图像中的文本的分量的第三映射。 将第二分类器应用于第三图，以生成标识图像中的文本的文本行的第四图。 文本区域定位器模块阈值第四个映射以识别图像中的文本区域。
-
-
-
-
-
-
-
-
-
Search Results
197
records
(took 0.026 seconds)
