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公开(公告)号：US20060104542A1
公开(公告)日：2006-05-18
申请号：US11213080
申请日：2005-08-26
IPC分类号： G06K9/36
摘要： An output image formed from at least a portion of one or more input images may be automatically synthesized as a tapestry image. To determine which portion or region of each input image will be used in the image tapestry, the regions of each image may be labeled by one of a plurality of labels. The multi-class labeling problem of creating the tapestry may be resolved such that each region in the tapestry is constructed from one or more salient input image regions that are selected and placed such that neighboring blocks in the tapestry satisfy spatial compatibility. This solution may be formulated using a Markov Random Field and the resulting tapestry energy function may be optimized in any suitable manner. To optimize the tapestry energy function, an expansion move algorithm for energy functions may be generated to apply to non-metric hard and/or soft constraints.
摘要翻译： 由一个或多个输入图像的至少一部分形成的输出图像可以自动合成为挂毯图像。 为了确定在图像挂毯中将使用每个输入图像的哪个部分或区域，每个图像的区域可以由多个标签之一标记。 可以解决创建挂毯的多类标签问题，使得挂毯中的每个区域由选择和放置的一个或多个显着输入图像区域构成，使得挂毯中的相邻块满足空间兼容性。 该解决方案可以使用马尔科夫随机场来形成，并且所得到的挂毯能量函数可以以任何合适的方式进行优化。 为了优化挂毯能量函数，可以产生用于能量函数的扩展移动算法以应用于非度量硬和/或软约束。
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公开(公告)号：US20090129700A1
公开(公告)日：2009-05-21
申请号：US11997033
申请日：2006-07-28
IPC分类号： G06K9/36
CPC分类号： G06T11/00
摘要： Previously, Poisson blending has been used for image blending including cloning an object onto a target background and blending pairs of source images together. Such Poisson blending works well in many situations. However, whilst this method is always workable, we have found that discolorations sometimes occur. We realized that these discolorations occur when the gradient of the source image is preserved too insistently, at the expense of preserving object and background color. In some situations object outlines become smeared or blurred. We develop a color preservation term and a fragility measure to address these problems. This gives a user additional control to obtain smooth compositions and reduce discoloration artifacts.
摘要翻译： 以前，Poisson混合已被用于图像混合，包括将对象克隆到目标背景上，并将一组源图像混合在一起。 这种泊松混合在许多情况下运作良好。 然而，虽然这种方法总是可行的，但我们发现有时会发生变色。 我们意识到，当源图像的梯度太保守地保留对象和背景色的代价时，会发生这些变色。 在某些情况下，对象轮廓变得模糊或模糊。 我们开发一个保色术语和一个脆弱的措施来解决这些问题。 这给予用户额外的控制以获得平滑的组合物并减少变色伪影。
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公开(公告)号：US08019177B2
公开(公告)日：2011-09-13
申请号：US11997033
申请日：2006-07-28
IPC分类号： G06K9/36
CPC分类号： G06T11/00
摘要： Previously, Poisson blending has been used for image blending including cloning an object onto a target background and blending pairs of source images together. Such Poisson blending works well in many situations. However, whilst this method is always workable, we have found that discolorations sometimes occur. We realized that these discolorations occur when the gradient of the source image is preserved too insistently, at the expense of preserving object and background color. In some situations object outlines become smeared or blurred. We develop a color preservation term and a fragility measure to address these problems. This gives a user additional control to obtain smooth compositions and reduce discoloration artifacts.
摘要翻译： 以前，Poisson混合已被用于图像混合，包括将对象克隆到目标背景上，并将一组源图像混合在一起。 这种泊松混合在许多情况下运作良好。 然而，虽然这种方法总是可行的，但我们发现有时会发生变色。 我们意识到，当源图像的梯度太保守地保留对象和背景色的代价时，会发生这些变色。 在某些情况下，对象轮廓变得模糊或模糊。 我们开发一个保色术语和一个脆弱的措施来解决这些问题。 这给予用户额外的控制以获得平滑的组合物并减少变色伪影。
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公开(公告)号：US20070031037A1
公开(公告)日：2007-02-08
申请号：US11195027
申请日：2005-08-02
CPC分类号： G06K9/00234 , G06K9/342 , G06K9/38 , G06K9/4652 , G06T7/11 , G06T7/162 , G06T7/194 , G06T2207/10021 , G06T2207/10024 , G06T2207/20072
摘要： Real-time segmentation of foreground from background layers in binocular video sequences may be provided by a segmentation process which may be based on one or more factors including likelihoods for stereo-matching, color, and optionally contrast, which may be fused to infer foreground and/or background layers accurately and efficiently. In one example, the stereo image may be segmented into foreground, background, and/or occluded regions using stereo disparities. The stereo-match likelihood may be fused with a contrast sensitive color model that is initialized or learned from training data. Segmentation may then be solved by an optimization algorithm such as dynamic programming or graph cut. In a second example, the stereo-match likelihood may be marginalized over foreground and background hypotheses, and fused with a contrast-sensitive color model that is initialized or learned from training data. Segmentation may then be solved by an optimization algorithm such as a binary graph cut.
摘要翻译： 可以通过分割过程来提供来自双目视频序列中的背景层的前景的实时分割，分割过程可以基于一个或多个因素，包括立体匹配，颜色和可选对比的可能性，其可以融合到推断前景和 /或背景层准确高效。 在一个示例中，立体图像可以使用立体声差异被分割成前景，背景和/或遮挡区域。 立体匹配似然率可以与从训练数据初始化或学习的对比度敏感颜色模型融合。 然后可以通过诸如动态规划或图形切割的优化算法来解决分割。 在第二个例子中，立体匹配似然度在前景和背景假设上可能被边缘化，并且与从训练数据初始化或学习的对比度敏感颜色模型融合。 然后可以通过诸如二进制图切割的优化算法来解决分割。
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公开(公告)号：US08041114B2
公开(公告)日：2011-10-18
申请号：US11764002
申请日：2007-06-15
IPC分类号： G06K9/34
摘要： Computer vision applications often require each pixel within an image to be assigned one of a set of labels. A method of improving the labels assigned to pixels is described which uses the quadratic pseudoboolean optimization (QPBO) algorithm. Starting with a partially labeled solution, an unlabeled pixel is assigned a value from a fully labeled reference solution and the energy of the partially labeled solution plus this additional pixel is calculated. The calculated energy is then used to generate a revised partially labeled solution using QPBO.
摘要翻译： 计算机视觉应用程序通常需要将图像中的每个像素分配给一组标签之一。 描述了改进分配给像素的标签的方法，其使用二次伪布尔优化（QPBO）算法。 从部分标记的解决方案开始，将未标记的像素从完全标记的参考解决方案中分配一个值，并计算部分标记溶液的能量加上该附加像素。 然后计算的能量用于使用QPBO产生修正的部分标记溶液。
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公开(公告)号：US20080310743A1
公开(公告)日：2008-12-18
申请号：US11764002
申请日：2007-06-15
IPC分类号： G06K9/36
摘要： Computer vision applications often require each pixel within an image to be assigned one of a set of labels. A method of improving the labels assigned to pixels is described which uses the quadratic pseudoboolean optimization (QPBO) algorithm. Starting with a partially labeled solution, an unlabeled pixel is assigned a value from a fully labeled reference solution and the energy of the partially labeled solution plus this additional pixel is calculated. The calculated energy is then used to generate a revised partially labeled solution using QPBO.
摘要翻译： 计算机视觉应用程序通常需要将图像中的每个像素分配给一组标签之一。 描述了改进分配给像素的标签的方法，其使用二次伪布尔优化（QPBO）算法。 从部分标记的解决方案开始，将未标记的像素从完全标记的参考解决方案中分配一个值，并计算部分标记溶液的能量加上该附加像素。 然后计算的能量用于使用QPBO产生修正的部分标记溶液。
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公开(公告)号：US08503783B2
公开(公告)日：2013-08-06
申请号：US13050825
申请日：2011-03-17
申请人： Carsten Rother , Victor Lempitsky , Andrew Blake
发明人： Carsten Rother , Victor Lempitsky , Andrew Blake
IPC分类号： G06K9/34
CPC分类号： G06K9/342 , G06K9/4638
摘要： A method of labeling pixels in an image is described where the pixel label is selected from a set of three or more labels. The pixel labeling problem is reduced to a sequence of binary optimizations by representing the label value for each pixel as a binary word and then optimizing the value of each bit within the word, starting with the most significant bit. Data which has been learned from one or more training images is used in the optimization to provide information about the less significant bits within the word.
摘要翻译： 描述了一种标记图像中的像素的方法，其中从一组三个或更多个标签中选择像素标签。 通过将每个像素的标签值表示为二进制字，然后优化字中每个位的值，从最高有效位开始，将像素标注问题简化为一系列二进制优化。 在优化中使用已经从一个或多个训练图像中学习的数据来提供关于该单词内较低有效位的信息。
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公开(公告)号：US20110274352A1
公开(公告)日：2011-11-10
申请号：US12776082
申请日：2010-05-07
申请人： Andrew Blake , Varun Gulshan , Carsten Rother , Antonio Criminisi
发明人： Andrew Blake , Varun Gulshan , Carsten Rother , Antonio Criminisi
IPC分类号： G06K9/34
CPC分类号： G06T7/11 , G06T7/194 , G06T2207/20101 , G06T2207/20168
摘要： Image segmentation using star-convexity constraints is described. In an example, user input specifies positions of one or more star centers in a foreground to be segmented from a background of an image. In embodiments, an energy function is used to express the problem of segmenting the image and that energy function incorporates a star-convexity constraint which limits the number of possible solutions. For example, the star-convexity constraint may be that, for any point p inside the foreground, all points on a shortest path (which may be geodesic or Euclidean) between the nearest star center and p also lie inside the foreground. In some examples continuous star centers such as lines are used. In embodiments a user may iteratively edit the star centers by adding brush strokes to the image in order to progressively change the star-convexity constraints and obtain an accurate segmentation.
摘要翻译： 描述了使用星形凸度约束的图像分割。 在一个示例中，用户输入指定要从图像的背景分割的前景中的一个或多个星形中心的位置。 在实施例中，能量函数用于表示分割图像的问题，并且能量函数包含限制可能解决方案数量的星形 - 凸度约束。 例如，星凸约束可以是，对于前景中的任何点p，最近的星中心和p之间的最短路径上的所有点（可以是测地线或欧几里德）也位于前景内。 在一些示例中，使用诸如线的连续星形中心。 在实施例中，用户可以通过向图像中添加画笔笔触来迭代地编辑星形中心，以逐渐改变星形凸度约束并获得准确的分割。
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公开(公告)号：US07925089B2
公开(公告)日：2011-04-12
申请号：US11857075
申请日：2007-09-18
申请人： Carsten Rother , Victor Lempitsky , Andrew Blake
发明人： Carsten Rother , Victor Lempitsky , Andrew Blake
IPC分类号： G06K9/34
CPC分类号： G06K9/342 , G06K9/4638
摘要： A method of labeling pixels in an image is described where the pixel label is selected from a set of three or more labels. The pixel labeling problem is reduced to a sequence of binary optimizations by representing the label value for each pixel as a binary word and then optimizing the value of each bit within the word, starting with the most significant bit. Data which has been learned from one or more training images is used in the optimization to provide information about the less significant bits within the word.
摘要翻译： 描述了一种标记图像中的像素的方法，其中从一组三个或更多个标签中选择像素标签。 通过将每个像素的标签值表示为二进制字，然后优化字中每个位的值，从最高有效位开始，将像素标注问题简化为一系列二进制优化。 在优化中使用已经从一个或多个训练图像中学习的数据来提供关于该单词内较低有效位的信息。
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公开(公告)号：US20100128984A1
公开(公告)日：2010-05-27
申请号：US12323355
申请日：2008-11-25
申请人： Victor Lempitsky , Carsten Rother , Andrew Blake
发明人： Victor Lempitsky , Carsten Rother , Andrew Blake
IPC分类号： G06K9/34
CPC分类号： G06K9/6224
摘要： An image processing system is described which automatically labels image elements of a digital image. In an embodiment an energy function describing the quality of possible labelings of an image is globally optimized to find an output labeled image. In the embodiment, the energy function comprises terms that depend on at least one non-local parameter. For example, the non-local parameter describes characteristics of image elements having the same label. In an embodiment the global optimization is achieved in a practical, efficient manner by using a tree structure to represent candidate values of the non-local parameter and by using a branch and bound process. In some embodiments, the branch and bound process comprises evaluating a lower bound of the energy function by using a min-cut process. For example, the min-cut process enables the lower bound to be evaluated efficiently using a graphical data structure to represent the lower bound.
摘要翻译： 描述了自动标记数字图像的图像元素的图像处理系统。 在一个实施例中，描述图像的可能标记的质量的能量函数被全局优化以找到输出标记图像。 在该实施例中，能量函数包括依赖于至少一个非局部参数的项。 例如，非本地参数描述具有相同标签的图像元素的特征。 在一个实施例中，通过使用树结构来表示非局部参数的候选值并且通过使用分支和绑定过程，以实用，有效的方式实现全局优化。 在一些实施例中，分支和绑定过程包括通过使用最小切割过程来评估能量函数的下限。 例如，最小切割过程使得能够使用图形数据结构有效地评估下限来表示下限。
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