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公开(公告)号：US20110216976A1
公开(公告)日：2011-09-08
申请号：US12718343
申请日：2010-03-05
IPC分类号： G06K9/34
CPC分类号： G06K9/34
摘要： Methods of updating image segmentation following user input are described. In an embodiment, the properties used in computing the different portions of the image are updated as a result of one or more user inputs. Image elements which have been identified by a user input are given more weight when updating the properties than other image elements which have already been assigned to a particular portion of the image. In another embodiment, an updated segmentation is post-processed such that only regions which are connected to an appropriate user input are updated.
摘要翻译： 描述用户输入后更新图像分割的方法。 在一个实施例中，用于计算图像的不同部分的属性被更新为一个或多个用户输入的结果。 当已经被分配给图像的特定部分的其他图像元素更新时，由用户输入识别的图像元素被赋予更多的权重。 在另一个实施例中，更新的分段被后处理，使得仅更新连接到适当的用户输入的区域。
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公开(公告)号：US20100220921A1
公开(公告)日：2010-09-02
申请号：US12780857
申请日：2010-05-14
申请人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
发明人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
IPC分类号： G06K9/00
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：US07653261B2
公开(公告)日：2010-01-26
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：US08655069B2
公开(公告)日：2014-02-18
申请号：US12718343
申请日：2010-03-05
IPC分类号： G06K9/34
CPC分类号： G06K9/34
摘要： Methods of updating image segmentation following user input are described. In an embodiment, the properties used in computing the different portions of the image are updated as a result of one or more user inputs. Image elements which have been identified by a user input are given more weight when updating the properties than other image elements which have already been assigned to a particular portion of the image. In another embodiment, an updated segmentation is post-processed such that only regions which are connected to an appropriate user input are updated.
摘要翻译： 描述用户输入后更新图像分割的方法。 在一个实施例中，用于计算图像的不同部分的属性被更新为一个或多个用户输入的结果。 当已经被分配给图像的特定部分的其他图像元素更新时，由用户输入识别的图像元素被赋予更多的权重。 在另一个实施例中，更新的分段被后处理，使得仅更新连接到适当的用户输入的区域。
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公开(公告)号：US07991228B2
公开(公告)日：2011-08-02
申请号：US12780857
申请日：2010-05-14
申请人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
发明人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
IPC分类号： G06K9/34
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：US08422769B2
公开(公告)日：2013-04-16
申请号：US12718321
申请日：2010-03-05
IPC分类号： G06K9/62
摘要： Methods of image segmentation using reduced foreground training data are described. In an embodiment, the foreground and background training data for use in segmentation of an image is determined by optimization of a modified energy function. The modified energy function is the energy function used in image segmentation with an additional term comprising a scalar value. The optimization is performed for different values of the scalar to produce multiple initial segmentations and one of these segmentations is selected based on pre-defined criteria. The training data is then used in segmenting the image. In other embodiments further methods are described: one places an ellipse inside the user-defined bounding box to define the background training data and another uses a comparison of properties of neighboring image elements, where one is outside the user-defined bounding box, to reduce the foreground training data.
摘要翻译： 描述使用减少的前景训练数据的图像分割方法。 在一个实施例中，用于图像分割的前景和背景训练数据通过改进的能量函数的优化来确定。 修改的能量函数是在图像分割中使用的能量函数，附加项包括标量值。 对标量的不同值执行优化以产生多个初始分段，并且基于预定义的标准来选择这些分段之一。 然后训练数据用于分割图像。 在其他实施例中，描述了进一步的方法：一个将椭圆放置在用户定义的边界框内以定义背景训练数据，另一个使用相邻图像元素的属性的比较，其中一个在用户定义的界限框之外，以减少 前台训练数据。
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公开(公告)号：US20110216965A1
公开(公告)日：2011-09-08
申请号：US12718321
申请日：2010-03-05
IPC分类号： G06K9/62
摘要： Methods of image segmentation using reduced foreground training data are described. In an embodiment, the foreground and background training data for use in segmentation of an image is determined by optimization of a modified energy function. The modified energy function is the energy function used in image segmentation with an additional term comprising a scalar value. The optimization is performed for different values of the scalar to produce multiple initial segmentations and one of these segmentations is selected based on pre-defined criteria. The training data is then used in segmenting the image. In other embodiments further methods are described: one places an ellipse inside the user-defined bounding box to define the background training data and another uses a comparison of properties of neighboring image elements, where one is outside the user-defined bounding box, to reduce the foreground training data.
摘要翻译： 描述使用减少的前景训练数据的图像分割方法。 在一个实施例中，用于图像分割的前景和背景训练数据通过改进的能量函数的优化来确定。 修改的能量函数是在图像分割中使用的能量函数，附加项包括标量值。 对标量的不同值执行优化以产生多个初始分段，并且基于预定义的标准来选择这些分段之一。 然后训练数据用于分割图像。 在其他实施例中，描述了进一步的方法：一个将椭圆放置在用户定义的边界框内以定义背景训练数据，另一个使用相邻图像元素的属性的比较，其中一个在用户定义的界限框之外，以减少 前台训练数据。
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公开(公告)号：US07720282B2
公开(公告)日：2010-05-18
申请号：US11195027
申请日：2005-08-02
申请人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
发明人： Andrew Blake , Antonio Criminisi , Geoffrey Cross , Vladimir Kolmogorov , Carsten Curt Eckard Rother
IPC分类号： G06K9/34
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段。
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公开(公告)号：US07430339B2
公开(公告)日：2008-09-30
申请号：US10914485
申请日：2004-08-09
IPC分类号： G06K9/36
CPC分类号： H04N5/275 , G06T7/12 , G06T7/162 , G06T7/194 , G06T2207/20041
摘要： Techniques are disclosed to provide more efficient and improved border matting for extracted foreground images, e.g., without requiring excessive user interaction. Border matting techniques described herein generate relatively continuous transparency (or alpha values) along the boundary of the extracted object (e.g., limiting color bleeding and/or artifacts).
摘要翻译： 公开了技术来提供用于提取的前景图像的更有效和改进的边缘消光，例如，不需要过度的用户交互。 本文描述的边缘消光技术沿着提取的对象的边界产生相对连续的透明度（或α值）（例如，限制颜色渗色和/或伪像）。
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公开(公告)号：US07660463B2
公开(公告)日：2010-02-09
申请号：US10861771
申请日：2004-06-03
CPC分类号： G06K9/342 , G06K9/00624 , G06K2209/015 , G06T7/11 , G06T7/162 , G06T7/194 , G06T2207/20072 , G06T2207/20104
摘要： Techniques are disclosed to provide more efficient and improved extraction of a portion of a scene without requiring excessive user interaction. More particularly, the extraction may be achieved by using iterated graph cuts. In an implementation, a method includes segmenting an image into a foreground portion and a background portion (e.g., where an object or desired portion to be extracted is present in the foreground portion). The method determines the properties corresponding to the foreground and background portions of the image. Distributions may be utilized to model the foreground and background properties. The properties may be color in one implementation and the distributions may be a Gaussian Mixture Model in another implementation. The foreground and background properties are updated based on the portions. And, the foreground and background portions are updated based on the updated foreground and background properties.
摘要翻译： 公开了技术来提供对场景的一部分的更有效和改进的提取，而不需要过度的用户交互。 更具体地，可以通过使用迭代图切割来实现提取。 在一个实现中，一种方法包括将图像分割成前景部分和背景部分（例如，在前景部分中存在要提取的对象或期望部分的位置）。 该方法确定与图像的前景和背景部分对应的属性。 可以使用分布来建模前景和背景属性。 在一个实现中，属性可以是颜色，并且在另一个实现中，分布可以是高斯混合模型。 前景和背景属性将根据部分进行更新。 并且，基于更新的前景和背景属性来更新前景和背景部分。
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