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1. 发明授权

US08351736B2 Automatic dust removal in digital images 有权
标题翻译：数字图像中自动除尘
公开(公告)号：US08351736B2
公开(公告)日：2013-01-08
申请号：US12476514
申请日：2009-06-02
申请人： Denis Demandolx , Eric Paul Bennett , Antonio Criminisi , Vladimir Farbman , Steven James White
发明人： Denis Demandolx , Eric Paul Bennett , Antonio Criminisi , Vladimir Farbman , Steven James White
IPC分类号： G06K9/40 , G06T5/00
CPC分类号： H04N5/3572 , H04N5/367 , H04N9/045
摘要： Methods and a processing device are provided for restoring pixels damaged by artifacts caused by dust, or other particles, entering a digital image capturing device. A user interface may be provided for a user to indicate an approximate location of an artifact appearing in a digital image. Dust attenuation may be estimated and an inverse transformation, based on the estimated dust attenuation, may be applied to damaged pixels in order to recover an estimate of the underlying digital image. One or many candidate source patch may be selected based on having smallest pixel distances, with respect to a target patch area. The damaged pixels included in the target patch area may be considered when calculating the pixel distance with respect to candidate source patches. RGB values of corresponding pixels of source patches may be used to restore the damaged pixels included in the target patch area.
摘要翻译：提供了方法和处理装置，用于恢复由于灰尘或其他颗粒引起的伪影所损坏的像素进入数字图像捕获装置。可以为用户提供用户界面来指示出现在数字图像中的人造物的大致位置。可以估计灰尘衰减，并且可以将基于估计的灰尘衰减的逆变换应用于损坏的像素，以便恢复底层数字图像的估计。可以基于相对于目标贴片区域具有最小像素距离来选择一个或多个候选源贴片。当计算相对于候选源贴片的像素距离时，可以考虑包括在目标贴片区域中的损伤像素。可以使用源贴片的相应像素的RGB值来恢复包括在目标贴片区域中的损伤像素。

2. 发明申请

US20100303380A1 Automatic Dust Removal In Digital Images 有权
标题翻译：数字图像中自动除尘
公开(公告)号：US20100303380A1
公开(公告)日：2010-12-02
申请号：US12476514
申请日：2009-06-02
申请人： Denis Demandolx , Eric Paul Bennett , Antonio Criminisi , Valadimir Farbman , Steven James White
发明人： Denis Demandolx , Eric Paul Bennett , Antonio Criminisi , Valadimir Farbman , Steven James White
IPC分类号： G06K9/40
CPC分类号： H04N5/3572 , H04N5/367 , H04N9/045
摘要： Methods and a processing device are provided for restoring pixels damaged by artifacts caused by dust, or other particles, entering a digital image capturing device. A user interface may be provided for a user to indicate an approximate location of an artifact appearing in a digital image. Dust attenuation may be estimated and an inverse transformation, based on the estimated dust attenuation, may be applied to damaged pixels in order to recover an estimate of the underlying digital image. One or many candidate source patch may be selected based on having smallest pixel distances, with respect to a target patch area. The damaged pixels included in the target patch area may be considered when calculating the pixel distance with respect to candidate source patches. RGB values of corresponding pixels of source patches may be used to restore the damaged pixels included in the target patch area.
摘要翻译：提供了方法和处理装置，用于恢复由于灰尘或其他颗粒引起的伪影所损坏的像素进入数字图像捕获装置。可以为用户提供用户界面来指示出现在数字图像中的人造物的大致位置。可以估计灰尘衰减，并且可以将基于估计的灰尘衰减的逆变换应用于损坏的像素，以便恢复底层数字图像的估计。可以基于相对于目标贴片区域具有最小像素距离来选择一个或多个候选源贴片。当计算相对于候选源贴片的像素距离时，可以考虑包括在目标贴片区域中的损伤像素。可以使用源贴片的相应像素的RGB值来恢复包括在目标贴片区域中的损伤像素。

3. 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。

4. 发明授权

US08571263B2 Predicting joint positions 有权
标题翻译：预测联合职位
公开(公告)号：US08571263B2
公开(公告)日：2013-10-29
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： G06K9/00
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。

5. 发明授权

US08558917B2 Transferring of digital images 有权
标题翻译：传输数字图像
公开(公告)号：US08558917B2
公开(公告)日：2013-10-15
申请号：US12096305
申请日：2006-11-24
申请人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , Mitch Goldberg , Carsten Rother , Antonio Criminisi , James Srinivasan
发明人： Kenneth Wood , Stephen Hodges , Lyndsay Williams , Mitch Goldberg , Carsten Rother , Antonio Criminisi , James Srinivasan
IPC分类号： H04N5/76 , H04N5/232 , H04W72/00 , H04W40/00 , H04W4/00 , G08C15/00
CPC分类号： H04N1/33353 , H04N1/00204 , H04N1/00307 , H04N1/32 , H04N2101/00 , H04N2201/0049 , H04N2201/0055
摘要： A method of transferring images from a first device to a second device and computer program code for performing this method is described. A connection characteristic for a connection between the first & second devices is determined and at least one image is selected from a plurality of images on the first device for transfer dependent upon both the connection characteristic and image selection criteria. The selected image(s) are then transferred over the connection from the first device to the second device.
摘要翻译：描述了将图像从第一设备传送到第二设备的方法以及用于执行该方法的计算机程序代码。确定第一和第二设备之间的连接的连接特性，并且取决于连接特性和图像选择标准两者，从用于传送的第一设备上的多个图像中选择至少一个图像。所选择的图像然后通过连接从第一设备传输到第二设备。

6. 发明授权

US08498481B2 Image segmentation using star-convexity constraints 有权
标题翻译：使用星形凸度约束的图像分割
公开(公告)号：US08498481B2
公开(公告)日：2013-07-30
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。

7. 发明授权

US08351654B2 Image processing using geodesic forests 有权
标题翻译：使用测地森林进行图像处理
公开(公告)号：US08351654B2
公开(公告)日：2013-01-08
申请号：US12431421
申请日：2009-04-28
申请人： Antonio Criminisi , Toby Sharp
发明人： Antonio Criminisi , Toby Sharp
IPC分类号： G06K9/00 , E04B7/08
CPC分类号： G06K9/6215 , G06T11/001
摘要： Image processing using geodesic forests is described. In an example, a geodesic forest engine determines geodesic shortest-path distances between each image element and a seed region specified in the image in order to form a geodesic forest data structure. The geodesic distances take into account gradients in the image of a given image modality such as intensity, color, or other modality. In some embodiments, a 1D processing engine carries out 1D processing along the branches of trees in the geodesic forest data structure to form a processed image. For example, effects such as ink painting, edge-aware texture flattening, contrast-aware image editing, forming animations using geodesic forests and other effects are achieved using the geodesic forest data structure. In some embodiments the geodesic forest engine uses a four-part raster scan process to achieve real-time processing speeds and parallelization is possible in many of the embodiments.
摘要翻译：描述了使用测地森林进行图像处理。在一个示例中，测地森林引擎确定每个图像元素与图像中指定的种子区域之间的测距最短路径距离，以形成测地森林数据结构。测距距离考虑了给定图像形态（如强度，颜色或其他形式）图像中的渐变。在一些实施例中，1D处理引擎沿着测地森林数据结构中的树的分支执行1D处理，以形成经处理的图像。例如，使用测地森林数据结构实现诸如水墨绘画，边缘感知纹理平整，对比度感知图像编辑，使用测地森林形成动画等效果。在一些实施例中，测地森林引擎使用四部分光栅扫描过程来实现实时处理速度，并且在许多实施例中并行化是可能的。

8. 发明申请

US20120166462A1 AUTOMATED IMAGE DATA PROCESSING AND VISUALIZATION 审中-公开
标题翻译：自动图像数据处理和可视化
公开(公告)号：US20120166462A1
公开(公告)日：2012-06-28
申请号：US12979362
申请日：2010-12-28
申请人： Sayan D. Pathak , Antonio Criminisi , Steven J. White , Liqun Fu , Khan M. Siddiqui , Toby Sharp , Ender Konukoglu , Bryan Dove , Michael T. Gillam
发明人： Sayan D. Pathak , Antonio Criminisi , Steven J. White , Liqun Fu , Khan M. Siddiqui , Toby Sharp , Ender Konukoglu , Bryan Dove , Michael T. Gillam
IPC分类号： G06F17/30 , G06F3/048
CPC分类号： G06F3/04845 , G06F3/04842 , G06F9/451 , G06F19/321 , G16H15/00 , G16H40/63
摘要： The present discussion relates to automated image data processing and visualization. One example can facilitate generating a graphical user-interface (GUI) from image data that includes multiple semantically-labeled user-selectable anatomical structures. This example can receive a user selection of an individual semantically-labeled user-selectable anatomical structure. The example can locate a sub-set of the image data associated with the individual semantically-labeled user-selectable anatomical structure and can cause presentation of the sub-set of the image data on a subsequent GUI.
摘要翻译：本发明涉及自动图像数据处理和可视化。一个示例可以有助于从包括多个语义标记的用户可选解剖结构的图像数据生成图形用户界面（GUI）。该示例可以接收用户选择单个语义标记的用户可选择的解剖结构。该示例可以定位与单独的语义标记的用户可选择的解剖结构相关联的图像数据的子集，并且可以在随后的GUI上引起图像数据的子集的呈现。

9. 发明授权

US08103109B2 Recognizing hand poses and/or object classes 有权
标题翻译：识别手姿势和/或对象类
公开(公告)号：US08103109B2
公开(公告)日：2012-01-24
申请号：US11765264
申请日：2007-06-19
申请人： John Winn , Antonio Criminisi , Ankur Agarwal , Thomas Deselaers
发明人： John Winn , Antonio Criminisi , Ankur Agarwal , Thomas Deselaers
IPC分类号： G06K9/62
CPC分类号： G06K9/00355 , G06F3/017 , G06F3/0425 , G06K9/6282
摘要： There is a need to provide simple, accurate, fast and computationally inexpensive methods of object and hand pose recognition for many applications. For example, to enable a user to make use of his or her hands to drive an application either displayed on a tablet screen or projected onto a table top. There is also a need to be able to discriminate accurately between events when a user's hand or digit touches such a display from events when a user's hand or digit hovers just above that display. A random decision forest is trained to enable recognition of hand poses and objects and optionally also whether those hand poses are touching or not touching a display surface. The random decision forest uses image features such as appearance, shape and optionally stereo image features. In some cases, the training process is cost aware. The resulting recognition system is operable in real-time.
摘要翻译：需要为许多应用提供简单，准确，快速和计算上便宜的对象和手姿态识别方法。例如，为了使用户能够利用他或她的手来驱动显示在平板电脑屏幕上或投影到桌面上的应用程序。当用户的手或数字在该显示器的正上方移动时，当用户的手或数字触发这样的显示时，还需要能够精确地区分事件之间的事件。训练随机决策林以识别手姿势和物体，并且还可以选择性地确定那些手姿势是触摸还是不接触显示表面。随机决策林使用图像特征，如外观，形状和可选的立体图像特征。在某些情况下，培训过程是意识到成本。所得到的识别系统可以实时操作。

10. 发明申请

US20110141121A1 Parallel Processing for Distance Transforms 有权
标题翻译：距离变换的并行处理
公开(公告)号：US20110141121A1
公开(公告)日：2011-06-16
申请号：US12635861
申请日：2009-12-11
申请人： Toby Sharp , Antonio Criminisi
发明人： Toby Sharp , Antonio Criminisi
IPC分类号： G06F15/80
CPC分类号： G06T17/10 , A63F2300/1087 , G06F17/10 , G06T5/30 , G06T2207/20041
摘要： Parallel processing for distance transforms is described. In an embodiment a raster scan algorithm is used to compute a distance transform such that each image element of a distance image is assigned a distance value. This distance value is a shortest distance from the image element to the seed region. In an embodiment two threads execute in parallel with a first thread carrying out a forward raster scan over the distance image and a second thread carrying out a backward raster scan over the image. In an example, a thread pauses when a cross-over condition is met until the other thread meets the condition after which both threads continue. In embodiments distances may be computed in Euclidean space or along geodesics defined on a surface. In an example, four threads execute two passes in parallel with each thread carrying out a raster scan over a different quarter of the image.
摘要翻译：描述了距离变换的并行处理。在一个实施例中，光栅扫描算法用于计算距离变换，使得距离图像的每个图像元素被分配距离值。该距离值是从图像元素到种子区域的最短距离。在一个实施例中，两个线程与第一线程并行执行，该第一线程在距离图像上执行正向光栅扫描，而第二线程在图像上执行向后光栅扫描。在一个示例中，当满足交叉条件时，线程将暂停，直到另一个线程满足两个线程继续的条件为止。在实施例中，距离可以在欧氏距离空间中或沿着表面上定义的测地线计算。在一个示例中，四个线程与在每个图像的不同四分之一处执行光栅扫描的每个线程并行执行两个遍。

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