公开(公告)号：US08625897B2

公开(公告)日：2014-01-07

申请号：US12790026

申请日：2010-05-28

Applicant: Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Andrew Fitzgibbon ,  Toby Sharp ,  Matthew Darius Cook

Inventor： Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Andrew Fitzgibbon ,  Toby Sharp ,  Matthew Darius Cook

IPC: G06K9/34

CPC classification number: G06K9/34 ,  G06K9/38 ,  G06T7/11 ,  G06T7/168 ,  G06T7/187 ,  G06T7/194 ,  G06T2207/10016 ,  G06T2207/20048 ,  G06T2207/20156 ,  G06T2207/30196 ,  H04N13/239

Abstract: Foreground and background image segmentation is described. In an example, a seed region is selected in a foreground portion of an image, and a geodesic distance is calculated from each image element to the seed region. A subset of the image elements having a geodesic distance less than a threshold is determined, and this subset of image elements are labeled as foreground. In another example, an image element from an image showing at least a user, a foreground object in proximity to the user, and a background is applied to trained decision trees to obtain probabilities of the image element representing one of these items, and a corresponding classification assigned to the image element. This is repeated for each image element. Image elements classified as belonging to the user are labeled as foreground, and image elements classified as foreground objects or background are labeled as background.

Abstract translation: 描述了前景和背景图像分割。 在一个示例中，在图像的前景部分中选择种子区域，并且从每个图像元素计算到种子区域的测地距离。 确定具有小于阈值的测地距离的图像元素的子集，并且该图像元素的子集被标记为前景。 在另一示例中，将来自显示至少用户的图像，邻近用户的前景对象和背景的图像元素应用于经过训练的决策树，以获得表示这些项目之一的图像元素的概率，以及相应的 分类到图像元素的分类。 对于每个图像元素重复这一点。 分类为属于用户的图像元素被标记为前景，并且被分类为前景对象或背景的图像元素被标记为背景。

公开(公告)号：US08437570B2

公开(公告)日：2013-05-07

申请号：US12126302

申请日：2008-05-23

Applicant: Antonio Criminisi ,  Toby Sharp

Inventor： Antonio Criminisi ,  Toby Sharp

IPC: G06K9/42 ,  G06K9/44 ,  G06K9/40

CPC classification number: G06T5/002 ,  G06K9/342 ,  G06T7/11 ,  G06T7/155 ,  G06T2207/10016 ,  G06T2207/30212

Abstract: A method of geodesic image and video processing is proposed. In an embodiment, the method uses a geodesic distance transform to construct an image filter. The filter can be used in a variety of image editing operations such as segmentation, denoising, texture smoothing, image stitching and cartooning. In one embodiment, the method may be made efficient by utilizing parallelism of the algorithm to carry out processing steps on at least two processing cores concurrently. This efficiency may enable high-resolution images and video to be processed at ‘real time’ rates without the need for specialist hardware.

Abstract translation: 提出了一种测地图像和视频处理方法。 在一个实施例中，该方法使用测地距离变换来构造图像滤波器。 滤镜可用于各种图像编辑操作，如分割，去噪，纹理平滑，图像拼接和卡通。 在一个实施例中，可以通过利用算法的并行性来同时对至少两个处理核执行处理步骤来使该方法有效。 这种效率可以使得高分辨率图像和视频以“实时”速率被处理，而不需要专用硬件。

公开(公告)号：US20130106994A1

公开(公告)日：2013-05-02

申请号：US13286966

申请日：2011-11-01

Applicant: Toby Sharp ,  Jamie Daniel Joseph Shotton

Inventor： Toby Sharp ,  Jamie Daniel Joseph Shotton

IPC: H04N13/00

CPC classification number: G06F3/038 ,  A63F13/42 ,  A63F2300/1093 ,  A63F2300/6045 ,  G06F3/017 ,  G06F3/0304 ,  G06K9/00335 ,  G06K9/00362 ,  G06K9/00369 ,  G06K9/00375 ,  G06K9/6269 ,  G06T2207/10028 ,  G06T2207/30196 ,  H04N19/597

Abstract: Depth image compression is described for example, to enable body-part centers of players of a game to be detected in real time from depth images or for other applications such as augmented reality, and human-computer interaction. In an embodiment, depth images which have associated body-part probabilities, are compressed using probability mass which is related to the depth of an image element and a probability of a body part for the image element. In various examples, compression of the depth images using probability mass enables body part center detection, by clustering output elements, to be speeded up. In some examples, the scale of the compression is selected according to a depth of a foreground region and in some cases different scales are used for different image regions. In some examples, certainties of the body-part centers are calculated using probability masses of clustered image elements.

Abstract translation: 例如，深度图像压缩被描述为使得能够从深度图像或诸如增强现实和人机交互的其他应用实时地检测游戏的玩家的身体部位中心。 在一个实施例中，具有相关联的身体部位概率的深度图像使用与图像元素的深度和图像元素的身体部位的概率相关的概率质量进行压缩。 在各种示例中，使用概率质量压缩深度图像可以通过聚类输出元素来加快身体部位中心检测。 在一些示例中，根据前景区域的深度选择压缩的比例，并且在一些情况下，不同的比例尺用于不同的图像区域。 在一些示例中，使用聚类图像元素的概率质量来计算身体部位中心的确定性。

公开(公告)号：US08290882B2

公开(公告)日：2012-10-16

申请号：US12248536

申请日：2008-10-09

Applicant: Toby Sharp

Inventor： Toby Sharp

IPC: G06E1/00

CPC classification number: G06N99/005

Abstract: Methods and apparatus for evaluating decision trees on a GPU are described. In an embodiment, the structure of a decision tree is converted into a 2D “tree” array with each row representing a node in the tree. Each row comprises details of any child nodes and the parameters which are required to perform the binary test at the node. A pixel shader can then be used to evaluate the decision tree in parallel for each input data point in an input array by navigating through rows in the 2D tree array. For each row, data is read from the input array dependent upon the parameters in the row and the shader moves to another row dependent upon the result of the binary test. On reaching a row which represents a leaf node, the pixel shader outputs evaluation results, such as a leaf node index or a probability distribution over classes.

Abstract translation: 描述了用于评估GPU上的决策树的方法和装置。 在一个实施例中，将决策树的结构转换为2D树数组，每行表示树中的节点。 每行包括任何子节点的细节和在节点执行二进制测试所需的参数。 然后可以使用像素着色器通过在2D树数组中的行进行导航来并行计算输入数组中每个输入数据点的决策树。 对于每一行，取决于行中的参数，从输入数组读取数据，并且着色器根据二进制测试的结果移动到另一行。 在到达表示叶节点的行时，像素着色器输出评估结果，例如叶节点索引或类上的概率分布。

公开(公告)号：US20110293180A1

公开(公告)日：2011-12-01

申请号：US12790026

申请日：2010-05-28

Applicant: Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Andrew Fitzgibbon ,  Toby Sharp ,  Matthew Darius Cook

Inventor： Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Andrew Fitzgibbon ,  Toby Sharp ,  Matthew Darius Cook

IPC: G06K9/34 ,  H04N13/02

CPC classification number: G06K9/34 ,  G06K9/38 ,  G06T7/11 ,  G06T7/168 ,  G06T7/187 ,  G06T7/194 ,  G06T2207/10016 ,  G06T2207/20048 ,  G06T2207/20156 ,  G06T2207/30196 ,  H04N13/239

Abstract: Foreground and background image segmentation is described. In an example, a seed region is selected in a foreground portion of an image, and a geodesic distance is calculated from each image element to the seed region. A subset of the image elements having a geodesic distance less than a threshold is determined, and this subset of image elements are labeled as foreground. In another example, an image element from an image showing at least a user, a foreground object in proximity to the user, and a background is applied to trained decision trees to obtain probabilities of the image element representing one of these items, and a corresponding classification assigned to the image element. This is repeated for each image element. Image elements classified as belonging to the user are labeled as foreground, and image elements classified as foreground objects or background are labeled as background.

Abstract translation: 描述了前景和背景图像分割。 在一个示例中，在图像的前景部分中选择种子区域，并且从每个图像元素计算到种子区域的测地距离。 确定具有小于阈值的测地距离的图像元素的子集，并且该图像元素的子集被标记为前景。 在另一示例中，将来自显示至少用户的图像，邻近用户的前景对象和背景的图像元素应用于经过训练的决策树，以获得表示这些项目之一的图像元素的概率，以及相应的 分类到图像元素的分类。 对于每个图像元素重复这一点。 分类为属于用户的图像元素被标记为前景，并且被分类为前景对象或背景的图像元素被标记为背景。

公开(公告)号：US20110228997A1

公开(公告)日：2011-09-22

申请号：US12725811

申请日：2010-03-17

Applicant: Toby Sharp ,  Antonio Criminisi ,  Khan Mohammad Siddiqui

Inventor： Toby Sharp ,  Antonio Criminisi ,  Khan Mohammad Siddiqui

IPC: G06K9/62

CPC classification number: G06T19/00 ,  G06T15/30 ,  G06T2200/24 ,  G06T2207/10081 ,  G06T2210/12 ,  G06T2219/004 ,  G06T2219/2012

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20110227934A1

公开(公告)日：2011-09-22

申请号：US12727849

申请日：2010-03-19

Applicant: Toby Sharp

Inventor： Toby Sharp

IPC: G06F15/16

CPC classification number: G06F19/321 ,  G06F9/5044 ,  G06F9/505 ,  G06F19/3418 ,  G06F2209/509

Abstract: Architecture for volume rendering is described. In an embodiment volume rendering is carried out at a data centre having a cluster of rendering servers connected using a high bandwidth connection to a database of medical volumes. For example, each rendering server has multiple graphics processing units each with a dedicated device thread. For example, a surgeon working from home on her netbook or thin client is able to have a medical volume rendered remotely at one of the rendering servers and the resulting 2D image sent to her over a relatively low bandwidth connection. In an example a master rendering server carries out load balancing at the cluster. In an example each rendering server uses a dedicated device thread for each graphics processing unit in its control and has multiple calling threads which are able to send rendering instructions to appropriate ones of the device threads.

Abstract translation: 描述体积渲染的体系结构。 在一个实施例中，在具有使用高带宽连接连接的呈现服务器的集群的数据中心上执行卷呈现到医疗卷的数据库。 例如，每个渲染服务器具有多个具有专用设备线程的图形处理单元。 例如，在家中在其上网本或瘦客户机上工作的外科医生能够在一个呈现服务器上远程呈现医疗卷，并且通过相对低带宽的连接发送给她的所得到的2D图像。 在一个示例中，主渲染服务器在集群上执行负载平衡。 在一个示例中，每个渲染服务器在其控制中为每个图形处理单元使用专用设备线程，并且具有能够将渲染指令发送到适当的设备线程的多个调用线程。

公开(公告)号：US20110216976A1

公开(公告)日：2011-09-08

申请号：US12718343

申请日：2010-03-05

Applicant: Carsten Curt Eckard Rother ,  Toby Sharp ,  Andrew Blake ,  Vladimir Kolmogorov

Inventor： Carsten Curt Eckard Rother ,  Toby Sharp ,  Andrew Blake ,  Vladimir Kolmogorov

IPC: G06K9/34

CPC classification number: G06K9/34

Abstract: 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.

Abstract translation: 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。