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1. 发明授权

US08724906B2 Computing pose and/or shape of modifiable entities 有权
标题翻译：计算可修改实体的姿态和/或形状
公开(公告)号：US08724906B2
公开(公告)日：2014-05-13
申请号：US13300542
申请日：2011-11-18
申请人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon , Jonathan James Taylor , Matthew Darius Cook
发明人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon , Jonathan James Taylor , Matthew Darius Cook
IPC分类号： G06K9/68 , G06K9/62
CPC分类号： G06K9/00214 , G06T7/75 , G06T17/00
摘要： Computing pose and/or shape of a modifiable entity is described. In various embodiments a model of an entity (such as a human hand, a golf player holding a golf club, an animal, a body organ) is fitted to an image depicting an example of the entity in a particular pose and shape. In examples, an optimization process finds values of pose and/or shape parameters that when applied to the model explain the image data well. In examples the optimization process is influenced by correspondences between image elements and model points obtained from a regression engine where the regression engine may be a random decision forest. For example, the random decision forest may take elements of the image and calculate candidate correspondences between those image elements and model points. In examples the model, pose and correspondences may be used for control of various applications including computer games, medical systems, augmented reality.
摘要翻译：描述可修改实体的计算姿势和/或形状。在各种实施例中，将实体（诸如人的手，持有高尔夫球杆，高尔夫球杆，动物，身体器官的高尔夫球手）的模型安装在描绘特定姿势和形状的实体的示例的图像上。在示例中，优化过程找到姿态和/或形状参数的值，当应用于模型时，可以很好地解释图像数据。在示例中，优化过程受图像元素和从回归引擎获得的模型点之间的对应性的影响，回归引擎可以是随机决策树。例如，随机决策树可以采用图像的元素，并计算这些图像元素和模型点之间的候选对应关系。在示例中，模型，姿态和对应可以用于控制各种应用，包括计算机游戏，医疗系统，增强现实。

2. 发明申请

US20100278384A1 Human body pose estimation 有权
标题翻译：人体姿势估计
公开(公告)号：US20100278384A1
公开(公告)日：2010-11-04
申请号：US12454628
申请日：2009-05-20
申请人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon
发明人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon
IPC分类号： G06K9/00 , G06K9/46
CPC分类号： G06K9/00335 , G06F3/017 , G06K9/00369 , G06T7/50 , G06T2207/10028 , G06T2207/20076 , G06T2207/30196
摘要： Techniques for human body pose estimation are disclosed herein. Depth map images from a depth camera may be processed to calculate a probability that each pixel of the depth map is associated with one or more segments or body parts of a body. Body parts may then be constructed of the pixels and processed to define joints or nodes of those body parts. The nodes or joints may be provided to a system which may construct a model of the body from the various nodes or joints.
摘要翻译：本文公开了人体姿势估计技术。可以处理来自深度相机的深度地图图像以计算深度图的每个像素与身体的一个或多个片段或身体部分相关联的概率。身体部位然后可以由像素构造并被处理以限定那些身体部位的关节或节点。节点或接头可以被提供给可以从各种节点或关节构造身体的模型的系统。

3. 发明申请

US20110210915A1 Human Body Pose Estimation 有权
标题翻译：人体姿势估计
公开(公告)号：US20110210915A1
公开(公告)日：2011-09-01
申请号：US13040205
申请日：2011-03-03
申请人： Jamie Daniel Joseph Shotton , Shahram Izadi , Otmar Hilliges , David Kim , David Geoffrey Molyneaux , Matthew Darius Cook , Pushmeet Kohli , Antonio Criminisi , Ross Brook Girshick , Andrew William Fitzgibbon
发明人： Jamie Daniel Joseph Shotton , Shahram Izadi , Otmar Hilliges , David Kim , David Geoffrey Molyneaux , Matthew Darius Cook , Pushmeet Kohli , Antonio Criminisi , Ross Brook Girshick , Andrew William Fitzgibbon
IPC分类号： G06K9/00 , G06F3/033
CPC分类号： G06K9/00369
摘要： Techniques for human body pose estimation are disclosed herein. Images such as depth images, silhouette images, or volumetric images may be generated and pixels or voxels of the images may be identified. The techniques may process the pixels or voxels to determine a probability that each pixel or voxel is associated with a segment of a body captured in the image or to determine a three-dimensional representation for each pixel or voxel that is associated with a location on a canonical body. These probabilities or three-dimensional representations may then be utilized along with the images to construct a posed model of the body captured in the image.
摘要翻译：本文公开了人体姿势估计技术。可以生成诸如深度图像，剪影图像或体积图像的图像，并且可以识别图像的像素或体素。这些技术可以处理像素或体素以确定每个像素或体素与在图像中捕获的身体的片段相关联的概率，或者确定与每个像素或体素上的位置相关联的每个像素或体素的三维表示规范身体。然后可以将这些概率或三维表示与图像一起使用以构建在图像中捕获的身体的姿态模型。

4. 发明授权

US08638985B2 Human body pose estimation 有权
标题翻译：人体姿势估计
公开(公告)号：US08638985B2
公开(公告)日：2014-01-28
申请号：US13040205
申请日：2011-03-03
申请人： Jamie Daniel Joseph Shotton , Shahram Izadi , Otmar Hilliges , David Kim , David Geoffrey Molyneaux , Matthew Darius Cook , Pushmeet Kohli , Antonio Criminisi , Ross Brook Girshick , Andrew William Fitzgibbon
发明人： Jamie Daniel Joseph Shotton , Shahram Izadi , Otmar Hilliges , David Kim , David Geoffrey Molyneaux , Matthew Darius Cook , Pushmeet Kohli , Antonio Criminisi , Ross Brook Girshick , Andrew William Fitzgibbon
IPC分类号： G06K9/00
CPC分类号： G06K9/00369
摘要： Techniques for human body pose estimation are disclosed herein. Images such as depth images, silhouette images, or volumetric images may be generated and pixels or voxels of the images may be identified. The techniques may process the pixels or voxels to determine a probability that each pixel or voxel is associated with a segment of a body captured in the image or to determine a three-dimensional representation for each pixel or voxel that is associated with a location on a canonical body. These probabilities or three-dimensional representations may then be utilized along with the images to construct a posed model of the body captured in the image.
摘要翻译：本文公开了人体姿势估计技术。可以生成诸如深度图像，剪影图像或体积图像的图像，并且可以识别图像的像素或体素。这些技术可以处理像素或体素以确定每个像素或体素与在图像中捕获的身体的片段相关联的概率，或者确定与每个像素或体素上的位置相关联的每个像素或体素的三维表示规范身体。然后可以将这些概率或三维表示与图像一起使用以构建在图像中捕获的身体的姿态模型。

5. 发明授权

US08503720B2 Human body pose estimation 有权
标题翻译：人体姿势估计
公开(公告)号：US08503720B2
公开(公告)日：2013-08-06
申请号：US12454628
申请日：2009-05-20
申请人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon
发明人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon
IPC分类号： G06K9/00
CPC分类号： G06K9/00335 , G06F3/017 , G06K9/00369 , G06T7/50 , G06T2207/10028 , G06T2207/20076 , G06T2207/30196
摘要： Techniques for human body pose estimation are disclosed herein. Depth map images from a depth camera may be processed to calculate a probability that each pixel of the depth map is associated with one or more segments or body parts of a body. Body parts may then be constructed of the pixels and processed to define joints or nodes of those body parts. The nodes or joints may be provided to a system which may construct a model of the body from the various nodes or joints.
摘要翻译：本文公开了人体姿势估计技术。可以处理来自深度相机的深度地图图像以计算深度图的每个像素与身体的一个或多个片段或身体部分相关联的概率。身体部位然后可以由像素构造并被处理以限定那些身体部位的关节或节点。节点或接头可以被提供给可以从各种节点或关节构造身体的模型的系统。

6. 发明申请

US20130129230A1 Computing Pose and/or Shape of Modifiable Entities 有权
标题翻译：可修改实体的计算姿势和/或形状
公开(公告)号：US20130129230A1
公开(公告)日：2013-05-23
申请号：US13300542
申请日：2011-11-18
申请人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon , Jonathan James Taylor , Matthew Darius Cook
发明人： Jamie Daniel Joseph Shotton , Andrew William Fitzgibbon , Jonathan James Taylor , Matthew Darius Cook
IPC分类号： G06K9/68
CPC分类号： G06K9/00214 , G06T7/75 , G06T17/00
摘要： Computing pose and/or shape of a modifiable entity is described. In various embodiments a model of an entity (such as a human hand, a golf player holding a golf club, an animal, a body organ) is fitted to an image depicting an example of the entity in a particular pose and shape. In examples, an optimization process finds values of pose and/or shape parameters that when applied to the model explain the image data well. In examples the optimization process is influenced by correspondences between image elements and model points obtained from a regression engine where the regression engine may be a random decision forest. For example, the random decision forest may take elements of the image and calculate candidate correspondences between those image elements and model points. In examples the model, pose and correspondences may be used for control of various applications including computer games, medical systems, augmented reality.
摘要翻译：描述可修改实体的计算姿势和/或形状。在各种实施例中，将实体（诸如人的手，持有高尔夫球杆，高尔夫球杆，动物，身体器官的高尔夫球手）的模型安装在描绘特定姿势和形状的实体的示例的图像上。在示例中，优化过程找到姿态和/或形状参数的值，当应用于模型时，可以很好地解释图像数据。在示例中，优化过程受图像元素和从回归引擎获得的模型点之间的对应性的影响，回归引擎可以是随机决策树。例如，随机决策树可以采用图像的元素，并计算这些图像元素和模型点之间的候选对应关系。在示例中，模型，姿态和对应可以用于控制各种应用，包括计算机游戏，医疗系统，增强现实。

7. 发明申请

US20150043770A1 SPECKLE SENSING FOR MOTION TRACKING 有权
标题翻译：用于运动跟踪的行星传感器
公开(公告)号：US20150043770A1
公开(公告)日：2015-02-12
申请号：US13963117
申请日：2013-08-09
申请人： Nicholas Yen-Cherng Chen , Stephen Edward Hodges , Andrew William Fitzgibbon , Andrew Clark Goris , Brian Lee Hastings , Shahram Izadi
发明人： Nicholas Yen-Cherng Chen , Stephen Edward Hodges , Andrew William Fitzgibbon , Andrew Clark Goris , Brian Lee Hastings , Shahram Izadi
IPC分类号： G06T7/00 , G06K9/00
CPC分类号： G06T7/0042 , G06F3/011 , G06F3/0304 , G06F3/0346 , G06K9/00208 , G06T7/73
摘要： Speckle sensing for motion tracking is described, for example, to track a user's finger or head in an environment to control a graphical user interface, to track a hand-held device, to track digits of a hand for gesture-based control, and to track 3D motion of other objects or parts of objects in a real-world environment. In various examples a stream of images of a speckle pattern from at least one coherent light source illuminating the object, or which is generated by a light source at the object to be tracked, is used to compute an estimate of 3D position of the object. In various examples the estimate is transformed using information about position and/or orientation of the object from another source. In various examples the other source is a time of flight system, a structured light system, a stereo system, a sensor at the object, or other sources.
摘要翻译：描述了用于运动跟踪的斑点感测，例如，在环境中跟踪用户的手指或头部以控制图形用户界面，跟踪手持设备，跟踪用于基于手势的控制的手的数字，以及跟踪现实环境中其他对象或物体部分的3D运动。在各种示例中，使用来自照亮对象的至少一个相干光源或由待跟踪对象上的光源产生的散斑图案的流图来计算对象的3D位置的估计。在各种示例中，使用关于来自另一来源的对象的位置和/或取向的信息来转换估计。在各种示例中，另一个来源是飞行时间系统，结构化光系统，立体声系统，物体上的传感器或其他来源。

8. 发明授权

US08543517B2 Distributed decision tree training 有权
标题翻译：分布式决策树训练
公开(公告)号：US08543517B2
公开(公告)日：2013-09-24
申请号：US12797430
申请日：2010-06-09
申请人： Jamie Shotton , Mihai-Dan Budiu , Andrew William Fitzgibbon , Mark Finocchio , Richard E. Moore , Duncan Robertson
发明人： Jamie Shotton , Mihai-Dan Budiu , Andrew William Fitzgibbon , Mark Finocchio , Richard E. Moore , Duncan Robertson
IPC分类号： G06F15/18
CPC分类号： G06K9/6282
摘要： A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.
摘要翻译：计算机化决策树训练系统可以包括配置成接收用于训练决策树的训练数据的输入的分布式控制处理单元。该系统还可以包括多个数据批处理单元，每个数据批处理单元被配置为评估用于训练数据的相应数据批的决策树的多个分离函数中的每一个，从而计算每个分割功能，用于数据批处理中的每个数据。该系统可以进一步包括多个节点批量处理单元，其被配置为针对每个分割函数聚合相关联的部分直方图，以形成用于边界树节点的子集中的每一个的每个分割函数的聚合直方图，并且为每个分割函数确定每个边缘树节点通过计算为边界树节点产生最高信息增益的分割函数。

9. 发明申请

US20140035901A1 ANIMATING OBJECTS USING THE HUMAN BODY 有权
标题翻译：使用人体的动画对象
公开(公告)号：US20140035901A1
公开(公告)日：2014-02-06
申请号：US13563313
申请日：2012-07-31
申请人： Jiawen Chen , Shahram Izadi , Andrew William Fitzgibbon
发明人： Jiawen Chen , Shahram Izadi , Andrew William Fitzgibbon
IPC分类号： G06T15/00
CPC分类号： G06T13/40 , A63F13/10 , A63F13/525 , G06T1/20 , G06T13/00 , G06T13/80
摘要： Methods of animating objects using the human body are described. In an embodiment, a deformation graph is generated from a mesh which describes the object. Tracked skeleton data is received which is generated from sensor data and the tracked skeleton is then embedded in the graph. Subsequent motion which is captured by the sensor result in motion of the tracked skeleton and this motion is used to define transformations on the deformation graph. The transformations are then applied to the mesh to generate an animation of the object which corresponds to the captured motion. In various examples, the mesh is generated by scanning an object and the deformation graph is generated using orientation-aware sampling such that nodes can be placed close together within the deformation graph where there are sharp corners or other features with high curvature in the object.
摘要翻译：描述使用人体对物体进行动画化的方法。在一个实施例中，从描述对象的网格生成变形图。从传感器数据生成跟踪的骨架数据，然后将跟踪的骨架嵌入到图中。由传感器捕获的随后的运动导致跟踪骨架的运动，并且该运动用于定义变形图上的变换。然后将变换应用于网格以生成对应于所捕获的运动的对象的动画。在各种示例中，通过扫描对象产生网格，并且使用取向感知采样生成变形图，使得节点可以在变形图中靠近放置，其中存在锐角或具有高曲率的其它特征。

10. 发明申请

US20110307423A1 DISTRIBUTED DECISION TREE TRAINING 有权
标题翻译：分布式决策树培训
公开(公告)号：US20110307423A1
公开(公告)日：2011-12-15
申请号：US12797430
申请日：2010-06-09
申请人： Jamie Shotton , Mihai-Dan Budiu , Andrew William Fitzgibbon , Mark Finocchio , Richard E. Moore , Duncan Robertson
发明人： Jamie Shotton , Mihai-Dan Budiu , Andrew William Fitzgibbon , Mark Finocchio , Richard E. Moore , Duncan Robertson
IPC分类号： G06F15/18 , G06K9/62
CPC分类号： G06K9/6282
摘要： A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.
摘要翻译：计算机化决策树训练系统可以包括配置成接收用于训练决策树的训练数据的输入的分布式控制处理单元。该系统还可以包括多个数据批处理单元，每个数据批处理单元被配置为评估用于训练数据的相应数据批的决策树的多个分离函数中的每一个，从而计算每个分割功能，用于数据批处理中的每个数据。该系统可以进一步包括多个节点批量处理单元，其被配置为针对每个分割函数聚合相关联的部分直方图，以形成用于边界树节点的子集中的每一个的每个分割函数的聚合直方图，并且为每个分割函数确定每个边缘树节点通过计算为边界树节点产生最高信息增益的分割函数。

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