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    Foreground and background image segmentation
    1.
    发明授权
    Foreground and background image segmentation 有权
    前景和背景图像分割

    公开(公告)号：US08625897B2

    公开(公告)日：2014-01-07

    申请号：US12790026

    申请日：2010-05-28

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

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

    IPC分类号： G06K9/34

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

    摘要： 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.

    摘要翻译： 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。

    Foreground and Background Image Segmentation
    2.
    发明申请
    Foreground and Background Image Segmentation 有权
    前景和背景图像分割

    公开(公告)号：US20110293180A1

    公开(公告)日：2011-12-01

    申请号：US12790026

    申请日：2010-05-28

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

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

    IPC分类号： G06K9/34 ,  H04N13/02

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

    摘要： 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.

    摘要翻译： 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。

    Predicting Joint Positions
    3.
    发明申请
    Predicting Joint Positions 有权
    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。

    Predicting joint positions
    4.
    发明授权
    Predicting joint positions 有权
    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。

    Reducing Interference Between Multiple Infra-Red Depth Cameras
    6.
    发明申请
    Reducing Interference Between Multiple Infra-Red Depth Cameras 有权
    减少多个红外深度相机之间的干扰

    公开(公告)号：US20120194650A1

    公开(公告)日：2012-08-02

    申请号：US13017518

    申请日：2011-01-31

    申请人： Shahram Izadi ,  David Molyneaux ,  Otmar Hilliges ,  David Kim ,  Jamie Daniel Joseph Shotton ,  Stephen Edward Hodges ,  David Alexander Butler ,  Andrew Fitzgibbon ,  Pushmeet Kohli

    发明人： Shahram Izadi ,  David Molyneaux ,  Otmar Hilliges ,  David Kim ,  Jamie Daniel Joseph Shotton ,  Stephen Edward Hodges ,  David Alexander Butler ,  Andrew Fitzgibbon ,  Pushmeet Kohli

    IPC分类号： H04N13/02

    CPC分类号： G06T7/55 ,  G01B9/08 ,  G01B11/22 ,  H04N5/23229 ,  H04N5/247 ,  H04N5/33 ,  H04N5/332 ,  H04N13/271

    摘要： Systems and methods for reducing interference between multiple infra-red depth cameras are described. In an embodiment, the system comprises multiple infra-red sources, each of which projects a structured light pattern into the environment. A controller is used to control the sources in order to reduce the interference caused by overlapping light patterns. Various methods are described including: cycling between the different sources, where the cycle used may be fixed or may change dynamically based on the scene detected using the cameras; setting the wavelength of each source so that overlapping patterns are at different wavelengths; moving source-camera pairs in independent motion patterns; and adjusting the shape of the projected light patterns to minimize overlap. These methods may also be combined in any way. In another embodiment, the system comprises a single source and a mirror system is used to cast the projected structured light pattern around the environment.

    摘要翻译： 描述了用于减少多个红外深度摄像机之间的干扰的系统和方法。 在一个实施例中，系统包括多个红外源，每个红外源将结构化的光图案投射到环境中。 控制器用于控制源，以减少由重叠的光图案引起的干扰。 描述了各种方法，包括：在不同的源之间循环，其中使用的周期可以是固定的，或者可以基于使用相机检测的场景动态地改变; 设置每个源的波长，使得重叠图案处于不同的波长; 以独立运动模式移动源摄像机对; 并调整投影光图案的形状以最小化重叠。 这些方法也可以以任何方式组合。 在另一个实施例中，系统包括单个源，并且使用镜子系统将投射的结构化光图案围绕环境投射。

    Generating computer models of 3D objects
    7.
    发明授权
    Generating computer models of 3D objects 有权
    生成3D对象的计算机模型

    公开(公告)号：US09053571B2

    公开(公告)日：2015-06-09

    申请号：US13154288

    申请日：2011-06-06

    申请人： Jamie Daniel Joseph Shotton ,  Shahram Izadi ,  Otmar Hilliges ,  David Kim ,  David Molyneaux ,  Pushmeet Kohli ,  Andrew Fitzgibbon ,  Stephen Edward Hodges

    发明人： Jamie Daniel Joseph Shotton ,  Shahram Izadi ,  Otmar Hilliges ,  David Kim ,  David Molyneaux ,  Pushmeet Kohli ,  Andrew Fitzgibbon ,  Stephen Edward Hodges

    IPC分类号： G06T17/00 ,  G06T15/00 ,  G06T17/10 ,  G06T7/20

    CPC分类号： G06T7/251 ,  G06T17/10 ,  G06T2200/08 ,  G06T2207/10028

    摘要： Generating computer models of 3D objects is described. In one example, depth images of an object captured by a substantially static depth camera are used to generate the model, which is stored in a memory device in a three-dimensional volume. Portions of the depth image determined to relate to the background are removed to leave a foreground depth image. The position and orientation of the object in the foreground depth image is tracked by comparison to a preceding depth image, and the foreground depth image is integrated into the volume by using the position and orientation to determine where to add data derived from the foreground depth image into the volume. In examples, the object is hand-rotated by a user before the depth camera. Hands that occlude the object are integrated out of the model as they do not move in sync with the object due to re-gripping.

    摘要翻译： 描述生成3D对象的计算机模型。 在一个示例中，使用由基本上静态的深度相机拍摄的对象的深度图像来生成存储在三维体积中的存储器设备中的模型。 确定与背景相关的深度图像的部分被去除以留下前景深度图像。 通过与前一个深度图像进行比较来跟踪前景深度图像中的对象的位置和方向，并且通过使用位置和方向来将前景深度图像集成到卷中，以确定在哪里添加从前景深度图像导出的数据 进入卷。 在示例中，该对象在深度相机之前由用户手动旋转。 闭合对象的手从模型中集成出来，因为它们不会因为重新抓取而与对象同步移动。

    Three-dimensional environment reconstruction
    10.
    发明授权
    Three-dimensional environment reconstruction 有权
    三维环境重建

    公开(公告)号：US08587583B2

    公开(公告)日：2013-11-19

    申请号：US13017690

    申请日：2011-01-31

    申请人： Richard Newcombe ,  Shahram Izadi ,  David Molyneaux ,  Otmar Hilliges ,  David Kim ,  Jamie Daniel Joseph Shotton ,  Stephen Edward Hodges ,  David Alexander Butler ,  Andrew Fitzgibbon ,  Pushmeet Kohli

    发明人： Richard Newcombe ,  Shahram Izadi ,  David Molyneaux ,  Otmar Hilliges ,  David Kim ,  Jamie Daniel Joseph Shotton ,  Stephen Edward Hodges ,  David Alexander Butler ,  Andrew Fitzgibbon ,  Pushmeet Kohli

    IPC分类号： G06T17/05 ,  G06T19/00

    CPC分类号： G06T17/00 ,  G06T2200/08

    摘要： Three-dimensional environment reconstruction is described. In an example, a 3D model of a real-world environment is generated in a 3D volume made up of voxels stored on a memory device. The model is built from data describing a camera location and orientation, and a depth image with pixels indicating a distance from the camera to a point in the environment. A separate execution thread is assigned to each voxel in a plane of the volume. Each thread uses the camera location and orientation to determine a corresponding depth image location for its associated voxel, determines a factor relating to the distance between the associated voxel and the point in the environment at the corresponding location, and updates a stored value at the associated voxel using the factor. Each thread iterates through an equivalent voxel in the remaining planes of the volume, repeating the process to update the stored value.

    摘要翻译： 描述了三维环境重建。 在一个示例中，在由存储在存储器件上的体素组成的3D体积中生成真实世界环境的3D模型。 该模型是从描述相机位置和方向的数据构建的，以及具有指示从相机到环境中的点的距离的像素的深度图像。 单独的执行线程被分配给卷的平面中的每个体素。 每个线程使用摄像机位置和方向来确定其相关体素的相应深度图像位置，确定与相关体素和相应位置处的环境中的点之间的距离有关的因子，并更新相关联的体素的存储值 体素使用因子。 每个线程遍历卷的剩余平面中的等效体素，重复更新存储值的过程。