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公开(公告)号：US20150139551A1
公开(公告)日：2015-05-21
申请号：US14081577
申请日：2013-11-15
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jonathan W. Brandt , Xiaohui Shen , Haoxiang Li
CPC classification number: G06K9/4604 , G06K9/6282 , G06K9/6857
Abstract: Cascaded object detection techniques are described. In one or more implementations, cascaded coarse-to-dense object detection techniques are utilized to detect objects in images. In a first stage, coarse features are extracted from an image, and non-object regions are rejected. Then, in one or more subsequent stages, dense features are extracted from the remaining non-rejected regions of the image to detect one or more objects in the image.
Abstract translation: 描述了级联对象检测技术。 在一个或多个实现中，使用级联的粗到密集对象检测技术来检测图像中的对象。 在第一阶段，从图像中提取粗糙特征，并且拒绝非对象区域。 然后，在一个或多个后续阶段，从图像的剩余未拒绝区域中提取密集特征以检测图像中的一个或多个对象。
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公开(公告)号：US09031345B2
公开(公告)日：2015-05-12
申请号：US13794408
申请日：2013-03-11
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
CPC classification number: G06T5/003 , G06T5/50 , G06T7/269 , G06T2207/10016
Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined. The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.
Abstract translation: 在考虑图像雾度的光学流量的实施例中，数字图像可以包括由数字图像中可见的雾度至少部分地模糊的对象，并且可以确定由数字图像中的雾度贡献的光的估计 。 可以基于由雾度贡献的光的估计，从数字图像中清除雾度，并且可以产生更清晰的数字图像。 然后可以计算更清晰的数字图像之间的光流，并且基于光流改进更清晰的数字图像，以在迭代过程中进一步清除来自图像的雾度，以提高数字图像中的对象的可视性。
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公开(公告)号：US20150116350A1
公开(公告)日：2015-04-30
申请号：US14062751
申请日：2013-10-24
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Peng Wang
IPC: G06T3/40
CPC classification number: G06T11/60 , G06T3/0012 , G06T2207/20132
Abstract: In techniques of combined composition and change-based models for image cropping, a composition application is implemented to apply one or more image composition modules of a learned composition model to evaluate multiple composition regions of an image. The learned composition model can determine one or more cropped images from the image based on the applied image composition modules, and evaluate a composition of the cropped images and a validity of change from the image to the cropped images. The image composition modules of the learned composition model include a salient regions module that iteratively determines salient image regions of the image, and include a foreground detection module that determines foreground regions of the image. The image composition modules also include one or more imaging models that reduce a number of the composition regions of the image to facilitate determining the cropped images from the image.
Abstract translation: 在用于图像裁剪的组合和基于变化的组合模型的技术中，实施组合应用以应用学习的组合模型的一个或多个图像组合模块来评估图像的多个组合区域。 所学习的构图模型可以基于所应用的图像组合模块从图像中确定一个或多个裁剪图像，并且评估裁剪图像的组成以及从图像到裁剪图像的变化的有效性。 所学习的构图模型的图像合成模块包括迭代地确定图像的显着图像区域的显着区域模块，并且包括确定图像的前景区域的前景检测模块。 图像合成模块还包括减少图像的合成区域的数量的一个或多个成像模型，以便于从图像确定裁剪的图像。
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公开(公告)号：US09002116B2
公开(公告)日：2015-04-07
申请号：US13782181
申请日：2013-03-01
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jonathan Brandt , Xiaohui Shen
CPC classification number: G06K9/6202 , G06K9/00228 , G06K2009/00328
Abstract: One exemplary embodiment involves identifying feature matches between each of a plurality of object images and a test image, each feature matches between a feature of a respective object image and a matching feature of the test image, wherein there is a spatial relationship between each respective object image feature and a test image feature, and wherein the object depicted in the test image comprises a plurality of attributes. Additionally, the embodiment involves estimating, for each attribute in the test image, an attribute value based at least in part on information stored in a metadata associated with each of the object images.
Abstract translation: 一个示例性实施例涉及识别多个对象图像和测试图像中的每一个之间的特征匹配，每个特征在相应对象图像的特征与测试图像的匹配特征之间匹配，其中每个相应对象之间存在空间关系 图像特征和测试图像特征，并且其中测试图像中描绘的对象包括多个属性。 另外，该实施例涉及至少部分地基于存储在与每个对象图像相关联的元数据中的信息来估计测试图像中的每个属性的属性值。
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公开(公告)号：US08989505B2
公开(公告)日：2015-03-24
申请号：US13713729
申请日：2012-12-13
Applicant: Adobe Systems Incorporated
Inventor： Kevin Armin Samii , Zhe Lin , Radomir Mech
CPC classification number: G06K9/6202 , G06K9/48 , G06K9/6215
Abstract: Systems and methods are provided for generating a distance metric. An image manipulation application receives first and second input images. The image manipulation application generates first and second sets of points corresponding to respective edges of a first object in the first input image and a second object in the second input image. The image manipulation application determines costs of arcs connecting each point from the first set to each point of the second set based on point descriptors for each point of each arc. The image manipulation application determines a minimum set of costs between the first set and the second set that includes a cost of each arc connecting each point of the second set to a point in the first set. The image manipulation application obtains, based at least in part on the minimum set of costs, a distance metric for first and second input images.
Abstract translation: 提供了用于产生距离度量的系统和方法。 图像处理应用接收第一和第二输入图像。 图像处理应用产生与第一输入图像中的第一对象的相应边缘相对应的第一和第二组点，以及第二输入图像中的第二对象。 图像处理应用程序确定基于每个弧的每个点的点描述符将每个点从第一组连接到第二组的每个点的弧的成本。 图像处理应用程序确定第一组和第二组之间的最小成本集合，其包括将第二组的每个点连接到第一组中的点的每个弧的成本。 图像处理应用至少部分地基于最小成本集获得第一和第二输入图像的距离度量。
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Patent Agency Ranking
156.发明申请公开(公告)号：US20150071561A1
公开(公告)日：2015-03-12
申请号：US14022462
申请日：2013-09-10
Applicant: Adobe Systems Incorporated
Inventor： Chih-Yao Hsieh , Yuyan Song , Zhe Lin
IPC: G06T5/00
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。
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公开(公告)号：US20140254943A1
公开(公告)日：2014-09-11
申请号：US13794408
申请日：2013-03-11
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
IPC: G06T5/00
CPC classification number: G06T5/003 , G06T5/50 , G06T7/269 , G06T2207/10016
Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.
Abstract translation: 在考虑图像雾度的光学流量的实施例中，数字图像可以包括由数字图像中可见的雾度至少部分地模糊的对象，并且可以确定由数字图像中的雾度贡献的光的估计 可以基于由雾度贡献的光的估计，从数字图像中清除雾度，并且可以产生更清晰的数字图像。 然后可以计算更清晰的数字图像之间的光流，并且基于光流改进更清晰的数字图像，以在迭代过程中进一步清除来自图像的雾度，以提高数字图像中的对象的可视性。
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公开(公告)号：US20140247993A1
公开(公告)日：2014-09-04
申请号：US13782804
申请日：2013-03-01
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Zhe Lin , Jonathan Brandt , Xiaohui Shen
IPC: G06T7/00
CPC classification number: G06T7/0079 , G06K9/00281
Abstract: One exemplary embodiment involves identifying feature matches between each of a plurality of object images and a test image, each of the feature matches between a feature of a respective object image and a matching feature of the test image, wherein there is a spatial relationship between each respective object image feature and a first landmark of the object image, the first landmark at a known location in the object image. The embodiment additionally involves estimating a plurality of locations for a second landmark for the test image, the estimated locations based at least in part on the feature matches and the spatial relationships, and estimating a final location for the second landmark from the plurality of locations for the second landmark for the test image.
Abstract translation: 一个示例性实施例涉及识别多个对象图像中的每一个与测试图像之间的特征匹配，每个特征在相应对象图像的特征与测试图像的匹配特征之间匹配，其中每个对象图像之间存在空间关系 对象图像的相应对象图像特征和第一界标，在对象图像中的已知位置处的第一界标。 该实施例另外包括估计用于测试图像的第二地标的多个位置，至少部分地基于特征匹配和空间关系估计位置，以及从多个位置估计第二地标的最终位置， 测试图像的第二个里程碑。
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公开(公告)号：US20140247963A1
公开(公告)日：2014-09-04
申请号：US13782735
申请日：2013-03-01
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jonathan Brandt , Xiaohui Shen
CPC classification number: G06K9/6202 , G06K9/00221 , G06K9/00228 , G06K9/3241 , G06K9/685
Abstract: One exemplary embodiment involves receiving, at a computing device comprising a processor, a test image having a candidate object and a set of object images detected to depict a similar object as the test image. The embodiment involves localizing the object depicted in each one of the object images based on the candidate object in the test image to determine a location of the object in each respective object image and then generating a validation score for the candidate object in the test image based at least in part on the determined location of the object in the respective object image and known location of the object in the same respective object image. The embodiment also involves computing a final detection score for the candidate object based on the validation score that indicates a confidence level that the object in the test image is located as indicated by the candidate object.
Abstract translation: 一个示例性实施例涉及在包括处理器的计算设备处接收具有候选对象的测试图像和检测到的用于描绘与测试图像相似的对象的一组对象图像。 该实施例涉及基于测试图像中的候选对象来定位每个对象图像中描绘的对象，以确定对象在每个相应对象图像中的位置，然后在基于测试图像的基础上生成候选对象的验证分数 至少部分地基于相应对象图像中的对象的确定位置和相同对象图像中的对象的已知位置。 该实施例还涉及基于指示由候选对象指示的测试图像中的对象所位于的置信水平的验证分数来计算候选对象的最终检测分数。
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公开(公告)号：US20190114818A1
公开(公告)日：2019-04-18
申请号：US15785386
申请日：2017-10-16
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: Predicting patch displacement maps using a neural network is described. Initially, a digital image on which an image editing operation is to be performed is provided as input to a patch matcher having an offset prediction neural network. From this image and based on the image editing operation for which this network is trained, the offset prediction neural network generates an offset prediction formed as a displacement map, which has offset vectors that represent a displacement of pixels of the digital image to different locations for performing the image editing operation. Pixel values of the digital image are copied to the image pixels affected by the operation by: determining the vectors pixels that correspond to the image pixels affected by the image editing operation and mapping the pixel values of the image pixels represented by the determined offset vectors to the affected pixels. According to this mapping, the pixel values of the affected pixels are set, effective to perform the image editing operation.
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