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61. 发明申请

US20110228997A1 Medical Image Rendering 有权
标题翻译：医学影像呈现
公开(公告)号：US20110228997A1
公开(公告)日：2011-09-22
申请号：US12725811
申请日：2010-03-17
申请人： Toby Sharp , Antonio Criminisi , Khan Mohammad Siddiqui
发明人： Toby Sharp , Antonio Criminisi , Khan Mohammad Siddiqui
IPC分类号： G06K9/62
CPC分类号： G06T19/00 , G06T15/30 , G06T2200/24 , G06T2207/10081 , G06T2210/12 , G06T2219/004 , G06T2219/2012
摘要： Medical image rendering is described. In an embodiment a medical image visualization engine receives results from an organ recognition system which provide estimated organ centers, bounding boxes and organ classification labels for a given medical image. In examples the visualization engine uses the organ recognition system results to select appropriate transfer functions, bounding regions, clipping planes and camera locations in order to optimally view an organ. For example, a rendering engine uses the selections to render a two-dimensional image of medical diagnostic quality with minimal user input. In an embodiment a graphical user interface populates a list of organs detected in a medical image and a clinician is able to select one organ and immediately be presented with the optimal view of that organ. In an example opacity of background regions of the medical image may be adjusted to provide context for organs presented in a foreground region.
摘要翻译：描述医学图像呈现。在一个实施例中，医学图像可视化引擎从提供给定医学图像的估计的器官中心，边界框和器官分类标签的器官识别系统接收结果。在示例中，可视化引擎使用器官识别系统结果来选择适当的传递函数，边界区域，剪切平面和相机位置，以便最佳地观察器官。例如，渲染引擎使用选择来以最小的用户输入呈现医学诊断质量的二维图像。在一个实施例中，图形用户界面填充在医学图像中检测到的器官的列表，并且临床医生能够选择一个器官并且立即呈现该器官的最佳视图。在示例性医学图像的背景区域的不透明度可以被调整以提供前景区域中呈现的器官的上下文。

62. 发明申请

US20100220921A1 STEREO IMAGE SEGMENTATION 有权
标题翻译：立体图像分割
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。

63. 发明授权

US07512262B2 Stereo-based image processing 有权
标题翻译：立体声图像处理
公开(公告)号：US07512262B2
公开(公告)日：2009-03-31
申请号：US11066946
申请日：2005-02-25
申请人： Antonio Criminisi , Andrew Blake , Geoffrey Cross
发明人： Antonio Criminisi , Andrew Blake , Geoffrey Cross
IPC分类号： G06K9/00
CPC分类号： G06K9/00241
摘要： Images of the same scene from multiple cameras may be use to generate a stereo disparity map. At least a portion of the stereo disparity map may be compared to a kernel image to detect and/or determine the location of an object in the disparity map. The kernel image is an array of pixel values which represent the stereo disparity of an object to be located, more particularly, the kernel image indicates the 3-dimensional surface shape of the object to be located from a point of view. The disparity map containing the located object may be process to manipulate the display of the stereo-based image and/or an input image. For example, the display of the image may be cropped and/or zoomed, areas of the image that are not the located object may be modified, an object such as an emoticon or smart-emoticon may be virtually inserted into the three dimensions of the image and may interact with the object, the location of the object in the image may localize further searches, presence of the located object in the image may indicate selected storing of the image and/or image indexing, and/or the located object in the image may be used as a non-standard input device to a computing system.
摘要翻译：可以使用来自多个摄像机的相同场景的图像来生成立体视差图。可以将立体视差图的至少一部分与核心图像进行比较，以检测和/或确定视差图中对象的位置。内核图像是表示要被定位的对象的立体视差的像素值的阵列，更具体地说，内核图像表示从一个角度来定位的对象的三维表面形状。包含定位对象的视差图可以是处理基于立体图像和/或输入图像的显示的处理。例如，可以裁剪和/或缩放图像的显示，可以修改不是定位对象的图像区域，诸如表情符号或智能表情符号的对象可以被虚拟地插入到图像并且可以与对象交互，图像中的对象的位置可以定位进一步的搜索，在图像中定位的对象的存在可以指示选择的图像和/或图像索引的存储和/或定位的对象在图像可以用作计算系统的非标准输入设备。

64. 发明授权

US07292735B2 Virtual image artifact detection 有权
标题翻译：虚拟图像伪像检测
公开(公告)号：US07292735B2
公开(公告)日：2007-11-06
申请号：US10826963
申请日：2004-04-16
申请人： Andrew Blake , Antonio Criminisi
发明人： Andrew Blake , Antonio Criminisi
IPC分类号： G06K9/36 , G06K9/00 , G06K9/40 , H04N1/409 , G06T5/00
CPC分类号： G06T5/005 , G06K9/03 , G06K9/20 , G06K2209/40 , G06T7/97 , G06T2207/10012 , G06T2207/10024 , H04N7/157 , H04N13/10
摘要： Artifacts are detected in a cyclopean virtual image generated from stereo images. A disparity map is generated from the stereo images. Individual projected images are determined based on the disparity map and the corresponding stereo images. A difference map is computed between the individual projected images to indicate the artifacts. A source patch in the virtual image is defined relative to an artifact. A replacement target patch is generated using a split-patch search technique as a composite of a background exemplar patch and a foreground exemplar patch. Each exemplar patch may be identified from an image patch selected from at least one of the stereo images. The source patch of the virtual image is replaced by the replacement target patch to correct the detected artifact.
摘要翻译：在从立体图像生成的环形虚拟图像中检测人造物。从立体图像生成视差图。基于视差图和对应的立体图像确定个体投影图像。在各个投影图像之间计算差异图，以指示伪像。虚拟映像中的源补丁是相对于工件定义的。使用分割补丁搜索技术来生成替换目标补丁作为背景示例补丁和前景示例补丁的组合。可以从选自至少一个立体图像的图像补丁来识别每个示例性补丁。虚拟映像的源修补程序将替换为替换目标修补程序，以更正检测到的伪像。

65. 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。

66. 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。

67. 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。

68. 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。

69. 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。

70. 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。

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