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公开(公告)号：US09342870B2
公开(公告)日：2016-05-17
申请号：US14060076
申请日：2013-10-22
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Hailin Jin
CPC classification number: G06T5/002 , G06T2207/20021
Abstract: Image denoising techniques are described. In one or more implementations, a denoising result is computed by a computing device for a patch of an image. One or more partitions are located by the computing device that correspond to the denoising result and a denoising operator is obtained by the computing device that corresponds to the located one or more partitions. The obtained denoising operator is applied by the computing device to the image.
Abstract translation: 描述了图像去噪技术。 在一个或多个实现中，由计算设备计算图像块的去噪结果。 一个或多个分区由计算设备定位，其对应于去噪结果，并且由与所定位的一个或多个分区相对应的计算设备获得去噪算子。 所获得的去噪算子由计算装置应用于图像。
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公开(公告)号：US20160132995A1
公开(公告)日：2016-05-12
申请号：US14539767
申请日：2014-11-12
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Byungmoon Kim , Yuan Gao
CPC classification number: G06K9/52 , G06K9/46 , G06K9/6215 , G06K2009/4666 , G06T5/002
Abstract: Structure aware image denoising and noise variance estimation techniques are described. In one or more implementations, structure-aware denoising is described which may take into account a structure of patches as part of the denoising operations. This may be used to select one or more reference patches for a pixel based on a structure of the patch, may be used to compute weights for patches that are to be used to denoised a pixel based on similarity of the patches, and so on. Additionally, implementations are described to estimate noise variance in an image using a map of patches of an image to identify regions having pixels having a variance that is below a threshold. The patches from the one or more regions may then be used to estimate noise variance for the image.
Abstract translation: 描述了结构感知图像去噪和噪声方差估计技术。 在一个或多个实现中，描述了可以考虑作为去噪操作的一部分的补丁的结构的结构感知去噪。 这可以用于基于补丁的结构为像素选择一个或多个参考补丁，可以用于基于补丁的相似性来计算要用于去除像素的补丁的权重，等等。 另外，描述了实现以使用图像的贴图来估计图像中的噪声方差，以识别具有低于阈值的方差的像素的区域。 然后可以使用来自一个或多个区域的补丁来估计图像的噪声方差。
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公开(公告)号：US20160104054A1
公开(公告)日：2016-04-14
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：US20160098823A1
公开(公告)日：2016-04-07
申请号：US14968075
申请日：2015-12-14
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 cropping s 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。
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公开(公告)号：US09286540B2
公开(公告)日：2016-03-15
申请号：US14085488
申请日：2013-11-20
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jianchao Yang , Hailin Jin , Xin Lu
CPC classification number: G06K9/4642 , G06K9/6273 , G06K9/6276
Abstract: In techniques for fast dense patch search and quantization, partition center patches are determined for partitions of example image patches. Patch groups of an image each include similar image patches and a reference image patch that represents a respective patch group. A partition center patch of the partitions is determined as a nearest neighbor to the reference image patch of a patch group. The partition center patch can be determined based on a single-nearest neighbor (1-NN) distance determination, and the determined partition center patch is allocated as the nearest neighbor to the similar image patches in the patch group. Alternatively, a group of nearby partition center patches are determined as the nearest neighbors to the reference image patch based on a k-nearest neighbor (k-NN) distance determination, and the nearest neighbor to each of the similar image patches in the patch group is determined from the nearby partition center patches.
Abstract translation: 在快速密集补丁搜索和量化的技术中，为示例图像补丁的分区确定分区中心补丁。 图像的补丁组各自包括相似的图像补丁和代表相应补丁组的参考图像补丁。 分区的分区中心补丁被确定为补丁组的参考图像补丁的最近邻。 可以基于单个最近邻居（1-NN）距离确定来确定分区中心补丁，并且将所确定的分区中心补丁分配为补丁组中的相似图像补丁的最近邻。 或者，基于k个最近邻（k-NN）距离确定，将一组附近的分区中心补丁确定为参考图像补丁的最近邻，并且补丁组中每个相似图像补丁的最近邻 是从附近的分区中心补丁确定的。
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Patent Agency Ranking
公开(公告)号：US09269017B2
公开(公告)日：2016-02-23
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：US09224066B2
公开(公告)日：2015-12-29
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：US09202138B2
公开(公告)日：2015-12-01
申请号：US13645463
申请日：2012-10-04
Applicant: Adobe Systems Incorporated
Inventor： Jonathan W. Brandt , Zhe Lin , Vuong Le , Lubomir D. Bourdev
CPC classification number: G06K9/6209 , G06K9/00228 , G06K9/2081 , G06K2009/366
Abstract: Various embodiments of methods and apparatus for feature point localization are disclosed. A profile model and a shape model may be applied to an object in an image to determine locations of feature points for each object component. Input may be received to move one of the feature points to a fixed location. Other ones of the feature points may be automatically adjusted to different locations based on the moved feature point.
Abstract translation: 公开了用于特征点定位的方法和装置的各种实施例。 轮廓模型和形状模型可以应用于图像中的对象，以确定每个对象分量的特征点的位置。 可以接收输入以将特征点中的一个移动到固定位置。 其他特征点可以根据所移动的特征点自动调整到不同的位置。
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公开(公告)号：US20150262336A1
公开(公告)日：2015-09-17
申请号：US14205027
申请日：2014-03-11
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zhuoyuan Chen , Scott D. Cohen , Jianchao Yang , Zhe Lin
CPC classification number: H04N5/21 , G06T3/4053 , G06T3/4076 , G06T5/002 , G06T5/003 , G06T5/20 , G06T5/50 , G06T7/269 , G06T2207/10016 , G06T2207/20021 , G06T2207/20032 , G06T2207/20182 , G06T2207/20201 , H04N5/144 , H04N5/145 , H04N5/147
Abstract: In techniques for video denoising using optical flow, image frames of video content include noise that corrupts the video content. A reference frame is selected, and matching patches to an image patch in the reference frame are determined from within the reference frame. A noise estimate is computed for previous and subsequent image frames relative to the reference frame. The noise estimate for an image frame is computed based on optical flow, and is usable to determine a contribution of similar motion patches to denoise the image patch in the reference frame. The similar motion patches from the previous and subsequent image frames that correspond to the image patch in the reference frame are determined based on the optical flow computations. The image patch is denoised based on an average of the matching patches from reference frame and the similar motion patches determined from the previous and subsequent image frames.
Abstract translation: 在使用光流的视频去噪的技术中，视频内容的图像帧包括破坏视频内容的噪声。 选择参考帧，并且从参考帧内确定参考帧中的图像块的匹配补丁。 针对相对于参考帧的先前和后续图像帧计算噪声估计。 基于光流计算图像帧的噪声估计，并且可用于确定类似运动补丁对参考帧中的图像补丁进行去噪的贡献。 基于光流计算确定与参考帧中的图像块相对应的来自先前和后续图像帧的类似运动补丁。 基于来自参考帧的匹配补丁的平均值和从先前和后续图像帧确定的类似运动补丁，去除图像补丁。
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公开(公告)号：US09129152B2
公开(公告)日：2015-09-08
申请号：US14080010
申请日：2013-11-14
Applicant: Adobe Systems Incorporated
Inventor： Jonathan Brandt , Zhe Lin , Brandon M. Smith
CPC classification number: G06K9/00295 , G06K9/00 , G06K9/00268 , G06K9/00275 , G06K9/4633 , G06K9/6215
Abstract: In an example embodiment, for each of the image exemplars, a first location offset between an actual landmark location for a first landmark in the image exemplar and a predicted landmark location for the first landmark in the image exemplar is determined. Then, a probability that the image recognition process applied using the first feature produces an accurate identification of the first landmark in the image exemplars is determined based on the first location offsets for each of the image exemplars. A weight may then be assigned to the first feature based on the derived probability. An image recognition process may then be performed on an image, the image recognition process utilizing a voting process, for each of one or more features, for one or more landmarks in the plurality of image exemplars, the voting process for the first feature weighted according to the weight assigned to the first feature.
Abstract translation: 在示例实施例中，对于每个图像样本，确定在图像样本中的第一地标的实际地标位置与图像样本中的第一地标的预测地标位置之间的第一位置偏移。 然后，基于每个图像样本的第一位置偏移来确定使用第一特征应用的图像识别处理产生图像样本中的第一地标的精确识别的概率。 然后可以基于导出的概率将权重分配给第一特征。 然后可以对图像执行图像识别处理，对于多个图像样本中的一个或多个地标，针对一个或多个特征中的每一个利用投票处理的图像识别处理，对第一特征的投票处理根据 分配给第一个特征的权重。
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