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61. 发明授权

US08954365B2 Density estimation and/or manifold learning 有权
标题翻译：密度估计和/或歧管学习
公开(公告)号：US08954365B2
公开(公告)日：2015-02-10
申请号：US13528866
申请日：2012-06-21
申请人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Ender Konukoglu
发明人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Ender Konukoglu
IPC分类号： G06F17/00 , G06K9/62
CPC分类号： G06K9/6232 , G06K9/6219 , G06K9/6226 , G06K9/6252
摘要： Density estimation and/or manifold learning are described, for example, for computer vision, medical image analysis, text document clustering. In various embodiments a density forest is trained using unlabeled data to estimate the data distribution. In embodiments the density forest comprises a plurality of random decision trees each accumulating portions of the training data into clusters at their leaves. In embodiments probability distributions representing the clusters at each tree are aggregated to form a forest density which is an estimate of a probability density function from which the unlabeled data may be generated. A mapping engine may use the clusters at the leaves of the density forest to estimate a mapping function which maps the unlabeled data to a lower dimensional space whilst preserving relative distances or other relationships between the unlabeled data points. A sampling engine may use the density forest to randomly sample data from the forest density.
摘要翻译：例如，对于计算机视觉，医学图像分析，文本文档聚类来描述密度估计和/或歧管学习。在各种实施例中，使用未标记的数据来训练密度森林以估计数据分布。在实施例中，密度森林包括多个随机决策树，每个随机决策树将训练数据的部分在其叶片上聚集成簇。在实施例中，表示每个树上的聚类的概率分布被聚合以形成森林密度，森林密度是可以从其生成未标记数据的概率密度函数的估计。映射引擎可以使用密度森林叶片处的簇来估计将未标记数据映射到较低维空间的映射函数，同时保留未标记数据点之间的相对距离或其他关系。采样引擎可以使用密度森林来从森林密度随机抽取数据。

62. 发明授权

US08867802B2 Automatic organ localization 有权
标题翻译：自动器官定位
公开(公告)号：US08867802B2
公开(公告)日：2014-10-21
申请号：US13090108
申请日：2011-04-19
申请人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Duncan Paul Robertson , Sayan D. Pathak , Steven James White , Khan Mohammed Siddiqui
发明人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Duncan Paul Robertson , Sayan D. Pathak , Steven James White , Khan Mohammed Siddiqui
IPC分类号： G06K9/00 , G06T7/00
CPC分类号： G06T7/0048 , G06K2209/051 , G06T7/77 , G06T2207/10072 , G06T2207/20076 , G06T2207/20081 , G06T2207/30004
摘要： Automatic organ localization is described. In an example, an organ in a medical image is localized using one or more trained regression trees. Each image element of the medical image is applied to the trained regression trees to compute probability distributions that relate to a distance from each image element to the organ. At least a subset of the probability distributions are selected and aggregated to calculate a localization estimate for the organ. In another example, the regression trees are trained using training images having a predefined organ location. At each node of the tree, test parameters are generated that determine which subsequent node each training image element is passed to. This is repeated until each image element reaches a leaf node of the tree. A probability distribution is generated and stored at each leaf node, based on the distance from the leaf node's image elements to the organ.
摘要翻译：描述自动器官定位。在一个示例中，使用一个或多个经过训练的回归树将医学图像中的器官定位。将医学图像的每个图像元素应用于经过训练的回归树，以计算与从每个图像元素到器官的距离相关的概率分布。选择和聚合概率分布的至少一个子集以计算器官的定位估计。在另一示例中，使用具有预定义的器官位置的训练图像来训练回归树。在树的每个节点，生成测试参数，确定每个训练图像元素传递到哪个后续节点。这是重复的，直到每个图像元素到达树的叶节点。基于从叶节点的图像元素到器官的距离，在每个叶节点处生成并存储概率分布。

63. 发明申请

US20130343619A1 DENSITY ESTIMATION AND/OR MANIFOLD LEARNING 有权
标题翻译：密度估算和/或差异学习
公开(公告)号：US20130343619A1
公开(公告)日：2013-12-26
申请号：US13528866
申请日：2012-06-21
申请人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Ender Konukoglu
发明人： Antonio Criminisi , Jamie Daniel Joseph Shotton , Ender Konukoglu
IPC分类号： G06K9/62
CPC分类号： G06K9/6232 , G06K9/6219 , G06K9/6226 , G06K9/6252
摘要： Density estimation and/or manifold learning are described, for example, for computer vision, medical image analysis, text document clustering. In various embodiments a density forest is trained using unlabeled data to estimate the data distribution. In embodiments the density forest comprises a plurality of random decision trees each accumulating portions of the training data into clusters at their leaves. In embodiments probability distributions representing the clusters at each tree are aggregated to form a forest density which is an estimate of a probability density function from which the unlabeled data may be generated. A mapping engine may use the clusters at the leaves of the density forest to estimate a mapping function which maps the unlabeled data to a lower dimensional space whilst preserving relative distances or other relationships between the unlabeled data points. A sampling engine may use the density forest to randomly sample data from the forest density.
摘要翻译：例如，对于计算机视觉，医学图像分析，文本文档聚类来描述密度估计和/或歧管学习。在各种实施例中，使用未标记的数据来训练密度森林以估计数据分布。在实施例中，密度森林包括多个随机决策树，每个随机决策树将训练数据的部分在其叶片上累积成簇。在实施例中，表示每个树上的聚类的概率分布被聚合以形成森林密度，森林密度是可以从其生成未标记数据的概率密度函数的估计。映射引擎可以使用密度森林叶片处的簇来估计将未标记数据映射到较低维空间的映射函数，同时保留未标记数据点之间的相对距离或其他关系。采样引擎可以使用密度森林来从森林密度随机抽取数据。

64. 发明授权

US08436852B2 Image editing consistent with scene geometry 有权
标题翻译：图像编辑与场景几何相一致
公开(公告)号：US08436852B2
公开(公告)日：2013-05-07
申请号：US12367675
申请日：2009-02-09
申请人： Antonio Criminisi , Carsten Rother , Gavin Smyth , Amit Shesh
发明人： Antonio Criminisi , Carsten Rother , Gavin Smyth , Amit Shesh
IPC分类号： G06T15/00
CPC分类号： G06T15/20 , G06T19/20 , G06T2200/24
摘要： Image editing which is consistent with geometry of a scene depicted in the image is described. In an embodiment a graphical user interface (GUI) is provided to enable a user to simply and quickly specify four corners of a rectangular frame drawn onto a source image using the GUI. In embodiments, the four corners are used to compute parameters of a virtual camera assumed to capture the image of the drawn frame. Embodiments of an image processing system are described which use the virtual camera parameters to control editing of the source image in ways consistent with the 3D geometry of the scene depicted in that image. In some embodiments out of bounds images are formed and/or realistic-looking shadows are synthesized. In examples, users are able to edit images and the virtual camera parameters are dynamically recomputed and used to update the edited image.
摘要翻译：描述与图像中描绘的场景的几何图形一致的图像编辑。在一个实施例中，提供图形用户界面（GUI）以使用户能够使用GUI简单快速地指定绘制到源图像上的矩形框架的四个角。在实施例中，四个角用于计算假定捕获所绘制的帧的图像的虚拟相机的参数。描述了图像处理系统的实施例，其使用虚拟相机参数来以与该图像中描绘的场景的3D几何形状一致的方式来控制源图像的编辑。在一些实施例中，形成图像外的图像和/或逼真的阴影被合成。在示例中，用户能够编辑图像，虚拟相机参数被动态重新计算并用于更新编辑的图像。

65. 发明申请

US20120239174A1 Predicting Joint Positions 有权
标题翻译：预测联合位置
公开(公告)号：US20120239174A1
公开(公告)日：2012-09-20
申请号：US13050858
申请日：2011-03-17
申请人： Jamie Daniel Joseph Shotton , Pushmeet Kohli , Ross Brook Girshick , Andrew Fitzgibbon , Antonio Criminisi
发明人： Jamie Daniel Joseph Shotton , Pushmeet Kohli , Ross Brook Girshick , Andrew Fitzgibbon , Antonio Criminisi
IPC分类号： G06F19/00 , G06K9/62 , G06K9/68
CPC分类号： G06F3/017 , G06K9/00362 , G06N5/025
摘要： Predicting joint positions is described, for example, to find joint positions of humans or animals (or parts thereof) in an image to control a computer game or for other applications. In an embodiment image elements of a depth image make joint position votes so that for example, an image element depicting part of a torso may vote for a position of a neck joint, a left knee joint and a right knee joint. A random decision forest may be trained to enable image elements to vote for the positions of one or more joints and the training process may use training images of bodies with specified joint positions. In an example a joint position vote is expressed as a vector representing a distance and a direction of a joint position from an image element making the vote. The random decision forest may be trained using a mixture of objectives.
摘要翻译：例如，描述关节位置的描述是为了在图像中找到人或动物（或其部分）的联合位置，以控制计算机游戏或用于其他应用。在一个实施例中，深度图像的图像元素进行联合位置投票，使得例如描绘躯干的一部分的图像元素可以投射颈部关节，左膝关节和右膝关节的位置。可以对随机决策林进行训练，以使图像元素能够对一个或多个关节的位置进行投票，并且训练过程可以使用具有指定关节位置的身体的训练图像。在一个例子中，联合立场表决被表示为表示从投票的图像元素的联合位置的距离和方向的向量。可以使用目标混合来训练随机决策林。

66. 发明授权

US08249397B2 Playback of digital images 有权
标题翻译：播放数字图像
公开(公告)号：US08249397B2
公开(公告)日：2012-08-21
申请号：US12096281
申请日：2006-11-16
申请人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , James Srinivasan , Carsten Rother , Antonio Criminisi
发明人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , James Srinivasan , Carsten Rother , Antonio Criminisi
IPC分类号： G06K9/54 , G06K9/60
CPC分类号： G06F17/30274 , G06F3/016 , G06F3/0481 , H04N1/00127 , H04N1/00442 , H04N1/00448 , H04N1/00458 , H04N1/00488 , H04N2201/3261
摘要： A method of displaying digital images is described in which a display length indicator is received and digital images are accessed. A set of digital images are selected from the accessed digital images in accordance with the display length indicator and displayed in a predetermined order. The method may be performed by a computer program, which may be embodied on a computer readable medium.
摘要翻译：描述显示数字图像的方法，其中接收显示长度指示符并访问数字图像。根据显示长度指示器从所访问的数字图像中选择一组数字图像，并以预定顺序显示。该方法可以由可以在计算机可读介质上体现的计算机程序来执行。

67. 发明申请

US20120207359A1 Image Registration 有权
标题翻译：图像注册
公开(公告)号：US20120207359A1
公开(公告)日：2012-08-16
申请号：US13025500
申请日：2011-02-11
申请人： Ender Konukoglu , Sayan Pathak , Khan Mohammad Siddiqui , Antonio Criminisi , Steven White , Jamie Daniel Joseph Shotton , Duncan Paul Robertson
发明人： Ender Konukoglu , Sayan Pathak , Khan Mohammad Siddiqui , Antonio Criminisi , Steven White , Jamie Daniel Joseph Shotton , Duncan Paul Robertson
IPC分类号： G06K9/00 , G06K9/32
CPC分类号： G06K9/6277 , G06K9/6282 , G06T7/35 , G06T2207/10072 , G06T2207/10116 , G06T2207/10132 , G06T2207/20072 , G06T2207/20076 , G06T2207/20081 , G06T2207/30004
摘要： Image registration is described. In an embodiment an image registration system executes automatic registration of images, for example medical images. In an example, semantic information is computed for each of the images to be registered comprising information about the types of objects in the images and the certainty of that information. In an example a mapping is found to register the images which takes into account the intensities of the image elements as well as the semantic information in a manner which is weighted by the certainty of that semantic information. For example, the semantic information is computed by estimating posterior distributions for the locations of anatomical structures by using a regression forest and transforming the posterior distributions into a probability map. In an example the mapping is found as a global point of inflection of an energy function, the energy function having a term related to the semantic information.
摘要翻译：描述图像注册。在一个实施例中，图像注册系统执行图像的自动注册，例如医学图像。在一个示例中，为要注册的每个图像计算语义信息，包括关于图像中的对象的类型和该信息的确定性的信息。在一个示例中，发现映射以以该语义信息的确定性加权的方式注册考虑了图像元素的强度以及语义信息的图像。例如，通过使用回归森林估计解剖结构的位置的后验分布并将后验分布变换为概率图来计算语义信息。在一个示例中，映射被发现为能量函数的拐点的全局点，能量函数具有与语义信息相关的术语。

68. 发明授权

US07840059B2 Object recognition using textons and shape filters 有权
标题翻译：使用纹理和形状过滤器的对象识别
公开(公告)号：US07840059B2
公开(公告)日：2010-11-23
申请号：US11534019
申请日：2006-09-21
申请人： John Winn , Carsten Rother , Antonio Criminisi , Jamie Shotton
发明人： John Winn , Carsten Rother , Antonio Criminisi , Jamie Shotton
IPC分类号： G06K9/62
CPC分类号： G06K9/3233 , G06K9/4604
摘要： Given an image of structured and/or unstructured objects we automatically partition it into semantically meaningful areas each labeled with a specific object class. We use a novel type of feature which we refer to as a shape filter. Shape filters enable us to capture some or all of shape, texture and appearance context information. A shape filter comprises one or more regions of arbitrary shape, size and position within a bounding area of an image, paired with a specified texton. A texton comprises information describing the texture of a patch of surface of an object. In a training process we select a sub-set of possible shape filters and incorporate those into a conditional random field model of object classes. That model is then used for object detection and recognition.
摘要翻译：给定结构化和/或非结构化对象的图像，我们自动将其划分为语义有意义的区域，每个区域都标有特定的对象类。我们使用一种我们称为形状滤波器的新型特征。形状过滤器使我们能够捕获部分或全部形状，纹理和外观上下文信息。形状滤波器包括在图像的边界区域内的任意形状，大小和位置的一个或多个区域，与指定的文本配对。文本包括描述对象的表面的纹理的信息。在训练过程中，我们选择可能的形状过滤器的子集，并将其合并到对象类的条件随机场模型中。然后将该模型用于对象检测和识别。

69. 发明申请

US20100201681A1 Image Editing Consistent with Scene Geometry 有权
标题翻译：图像编辑与场景几何一致
公开(公告)号：US20100201681A1
公开(公告)日：2010-08-12
申请号：US12367675
申请日：2009-02-09
申请人： Antonio Criminisi , Carsten Rother , Gavin Smyth , Amit Shesh
发明人： Antonio Criminisi , Carsten Rother , Gavin Smyth , Amit Shesh
IPC分类号： G06T15/00 , G09G5/00
CPC分类号： G06T15/20 , G06T19/20 , G06T2200/24
摘要： Image editing which is consistent with geometry of a scene depicted in the image is described. In an embodiment a graphical user interface (GUI) is provided to enable a user to simply and quickly specify four corners of a rectangular frame drawn onto a source image using the GUI. In embodiments, the four corners are used to compute parameters of a virtual camera assumed to capture the image of the drawn frame. Embodiments of an image processing system are described which use the virtual camera parameters to control editing of the source image in ways consistent with the 3D geometry of the scene depicted in that image. In some embodiments out of bounds images are formed and/or realistic-looking shadows are synthesized. In examples, users are able to edit images and the virtual camera parameters are dynamically recomputed and used to update the edited image.
摘要翻译：描述与图像中描绘的场景的几何图形一致的图像编辑。在一个实施例中，提供图形用户界面（GUI）以使用户能够使用GUI简单快速地指定绘制到源图像上的矩形框架的四个角。在实施例中，四个角用于计算假定捕获所绘制的帧的图像的虚拟相机的参数。描述了图像处理系统的实施例，其使用虚拟相机参数来以与该图像中描绘的场景的3D几何形状一致的方式来控制源图像的编辑。在一些实施例中，形成图像外的图像和/或逼真的阴影被合成。在示例中，用户能够编辑图像，虚拟相机参数被动态重新计算并用于更新编辑的图像。

70. 发明申请

US20100171846A1 Automatic Capture Modes 有权
标题翻译：自动捕获模式
公开(公告)号：US20100171846A1
公开(公告)日：2010-07-08
申请号：US12096235
申请日：2006-11-16
申请人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , James Srinivasan , Carsten Rother , Antonio Criminisi , John Chiloyan
发明人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , James Srinivasan , Carsten Rother , Antonio Criminisi , John Chiloyan
IPC分类号： H04N5/228 , H04N5/76
CPC分类号： H04N5/232 , G06F19/00 , H04N1/00323 , H04N1/2112 , H04N5/23245 , H04N2201/212
摘要： An image capture device is described which is operable in any one of a number of capture modes. The device comprises a camera, a memory and a processor. The memory stores a plurality of sets of capture triggers, with each set of capture triggers being associated with one of the plurality of capture modes. The processor selects one of the plurality of capture modes, such that the device is operable in the selected capture mode. In the selected capture mode, an image is captured automatically when a capture trigger within the associated set of capture triggers is satisfied.
摘要翻译：描述了可以以多种捕获模式中的任何一种操作的图像捕获装置。该装置包括相机，存储器和处理器。存储器存储多组捕获触发，其中每组捕获触发与多个捕获模式之一相关联。所述处理器选择所述多个捕获模式之一，使得所述设备在所选择的捕获模式中可操作。在选择的拍摄模式下，当相关联的捕捉触发组中的捕获触发被满足时，会自动捕获图像。

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