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公开(公告)号：US20110228976A1
公开(公告)日：2011-09-22
申请号：US12727787
申请日：2010-03-19
申请人： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
发明人： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
CPC分类号： G06K9/6256 , G06K9/00335 , G06K9/6206
摘要： Synthesized body images are generated for a machine learning algorithm of a body joint tracking system. Frames from motion capture sequences are retargeted to several different body types, to leverage the motion capture sequences. To avoid providing redundant or similar frames to the machine learning algorithm, and to provide a compact yet highly variegated set of images, dissimilar frames can be identified using a similarity metric. The similarity metric is used to locate frames which are sufficiently distinct, according to a threshold distance. For realism, noise is added to the depth images based on noise sources which a real world depth camera would often experience. Other random variations can be introduced as well. For example, a degree of randomness can be added to retargeting. For each frame, the depth image and a corresponding classification image, with labeled body parts, are provided. 3-D scene elements can also be provided.
摘要翻译： 为身体关节跟踪系统的机器学习算法生成合成身体图像。 来自运动捕捉序列的帧被重定向到几种不同的身体类型，以利用运动捕捉序列。 为了避免向机器学习算法提供冗余或相似的帧，并且为了提供紧凑但高度变化的图像集合，可以使用相似性度量来识别不同的帧。 相似性度量用于根据阈值距离定位足够明显的帧。 对于现实主义，基于真实世界深度相机经常会遇到的噪声源，将噪声添加到深度图像。 也可以引入其他随机变化。 例如，可以添加一定程度的随机性来重定向。 对于每个帧，提供深度图像和具有标记的身体部分的相应分类图像。 也可以提供3-D场景元素。
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公开(公告)号：US08213680B2
公开(公告)日：2012-07-03
申请号：US12727787
申请日：2010-03-19
申请人： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
发明人： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
CPC分类号： G06K9/6256 , G06K9/00335 , G06K9/6206
摘要： Synthesized body images are generated for a machine learning algorithm of a body joint tracking system. Frames from motion capture sequences are retargeted to several different body types, to leverage the motion capture sequences. To avoid providing redundant or similar frames to the machine learning algorithm, and to provide a compact yet highly variegated set of images, dissimilar frames can be identified using a similarity metric. The similarity metric is used to locate frames which are sufficiently distinct, according to a threshold distance. For realism, noise is added to the depth images based on noise sources which a real world depth camera would often experience. Other random variations can be introduced as well. For example, a degree of randomness can be added to retargeting. For each frame, the depth image and a corresponding classification image, with labeled body parts, are provided. 3-D scene elements can also be provided.
摘要翻译： 为身体关节跟踪系统的机器学习算法生成合成身体图像。 来自运动捕捉序列的帧被重定向到几种不同的身体类型，以利用运动捕捉序列。 为了避免向机器学习算法提供冗余或相似的帧，并且为了提供紧凑但高度变化的图像集合，可以使用相似性度量来识别不同的帧。 相似性度量用于根据阈值距离定位足够明显的帧。 对于现实主义，基于真实世界深度相机经常会遇到的噪声源，将噪声添加到深度图像。 也可以引入其他随机变化。 例如，可以添加一定程度的随机性来重定向。 对于每个帧，提供深度图像和具有标记的身体部分的相应分类图像。 也可以提供3-D场景元素。
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公开(公告)号：US08379919B2
公开(公告)日：2013-02-19
申请号：US12770394
申请日：2010-04-29
IPC分类号： G06K9/00
CPC分类号： G06K9/00375 , G06F3/017 , G06K9/342 , G06K9/6219 , H04N19/436
摘要： Systems and methods are disclosed for identifying objects captured by a depth camera by condensing classified image data into centroids of probability that captured objects are correctly identified entities. Output exemplars are processed to detect spatially localized clusters of non-zero probability pixels. For each cluster, a centroid is generated, generally resulting in multiple centroids for each differentiated object. Each centroid may be assigned a confidence value, indicating the likelihood that it corresponds to a true object, based on the size and shape of the cluster, as well as the probabilities of its constituent pixels.
摘要翻译： 公开了系统和方法，用于通过将分类的图像数据聚焦成捕获的对象被正确识别的实体的概率的质心来识别由深度相机捕获的对象。 处理输出样本以检测非零概率像素的空间局部集群。 对于每个聚类，生成质心，通常会为每个不同对象产生多个质心。 可以根据群集的大小和形状以及其组成像素的概率为每个质心分配置信度值，指示其对应于真实对象的可能性。
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公开(公告)号：US20110268316A1
公开(公告)日：2011-11-03
申请号：US12770394
申请日：2010-04-29
CPC分类号： G06K9/00375 , G06F3/017 , G06K9/342 , G06K9/6219 , H04N19/436
摘要： Systems and methods are disclosed for identifying objects captured by a depth camera by condensing classified image data into centroids of probability that captured objects are correctly identified entities. Output exemplars are processed to detect spatially localized clusters of non-zero probability pixels. For each cluster, a centroid is generated, generally resulting in multiple centroids for each differentiated object. Each centroid may be assigned a confidence value, indicating the likelihood that it corresponds to a true object, based on the size and shape of the cluster, as well as the probabilities of its constituent pixels.
摘要翻译： 公开了系统和方法，用于通过将分类的图像数据聚焦成捕获的对象被正确识别的实体的概率的质心来识别由深度相机捕获的对象。 处理输出样本以检测非零概率像素的空间局部集群。 对于每个聚类，生成质心，通常会为每个不同对象产生多个质心。 可以根据群集的大小和形状以及其组成像素的概率为每个质心分配置信度值，指示其对应于真实对象的可能性。
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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
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。
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公开(公告)号：US08570320B2
公开(公告)日：2013-10-29
申请号：US13017729
申请日：2011-01-31
申请人： Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
发明人： Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
CPC分类号： G06F3/011 , A63F13/65 , A63F2300/1087 , A63F2300/6009 , G06T7/20 , G06T17/00 , G06T2207/10016 , G06T2207/10028 , G06T2207/30244
摘要： Use of a 3D environment model in gameplay is described. In an embodiment, a mobile depth camera is used to capture a series of depth images as it is moved around and a dense 3D model of the environment is generated from this series of depth images. This dense 3D model is incorporated within an interactive application, such as a game. The mobile depth camera is then placed in a static position for an interactive phase, which in some examples is gameplay, and the system detects motion of a user within a part of the environment from a second series of depth images captured by the camera. This motion provides a user input to the interactive application, such as a game. In further embodiments, automatic recognition and identification of objects within the 3D model may be performed and these identified objects then change the way that the interactive application operates.
摘要翻译： 描述了在游戏中使用3D环境模型。 在一个实施例中，移动深度相机被用来捕获一系列深度图像，因为它被移动，并且从该系列深度图像生成环境的密集3D模型。 这种密集的3D模型被并入在诸如游戏的交互式应用中。 然后将移动深度相机放置在用于交互式相位的静态位置，在一些示例中为游戏画面，并且系统从相机拍摄的第二系列深度图像中检测环境部分内的用户的运动。 该运动向诸如游戏的交互式应用提供用户输入。 在另外的实施例中，可以执行3D模型内的对象的自动识别和识别，并且这些识别的对象然后改变交互式应用程序的操作方式。
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公开(公告)号：US08346800B2
公开(公告)日：2013-01-01
申请号：US12417511
申请日：2009-04-02
IPC分类号： G06F17/30
CPC分类号： G06K9/6257 , G06F17/30705 , G06F17/3071
摘要： Content-based information retrieval is described. In an example, a query item such as an image, document, email or other item is presented and items with similar content are retrieved from a database of items. In an example, each time a query is presented, a classifier is formed based on that query and using a training set of items. For example, the classifier is formed in real-time and is formed in such a way that a limit on the proportion of the items in the database that will be retrieved is set. In an embodiment, the query item is analyzed to identify tokens in that item and subsets of those tokens are selected to form the classifier. For example, the subsets of tokens are combined using Boolean operators in a manner which is efficient for searching on particular types of database.
摘要翻译： 描述基于内容的信息检索。 在一个示例中，呈现诸如图像，文档，电子邮件或其他项目的查询项目，并且从项目的数据库检索具有相似内容的项目。 在一个示例中，每次呈现查询时，基于该查询并使用项目的训练集形成分类器。 例如，分类器是实时形成的，并且以这样的方式形成：设置将要检索的数据库中的项目的比例的限制。 在一个实施例中，分析查询项目以识别该项目中的令牌，并且选择那些令牌的子集以形成分类器。 例如，使用布尔运算符组合令牌的子集，其方法对于在特定类型的数据库上进行搜索是有效的。
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公开(公告)号：US20120194644A1
公开(公告)日：2012-08-02
申请号：US13017474
申请日：2011-01-31
申请人： Richard Newcombe , Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
发明人： Richard Newcombe , Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
IPC分类号： H04N5/225
CPC分类号： G06T7/20 , G06T7/74 , G06T2207/10016 , G06T2207/10021 , G06T2207/10024 , G06T2207/10028 , G06T2207/30244
摘要： Mobile camera localization using depth maps is described for robotics, immersive gaming, augmented reality and other applications. In an embodiment a mobile depth camera is tracked in an environment at the same time as a 3D model of the environment is formed using the sensed depth data. In an embodiment, when camera tracking fails, this is detected and the camera is relocalized either by using previously gathered keyframes or in other ways. In an embodiment, loop closures are detected in which the mobile camera revisits a location, by comparing features of a current depth map with the 3D model in real time. In embodiments the detected loop closures are used to improve the consistency and accuracy of the 3D model of the environment.
摘要翻译： 使用深度图的移动摄像机定位被描述为机器人，沉浸式游戏，增强现实和其他应用。 在一个实施例中，移动深度相机在环境中跟踪，同时使用感测的深度数据形成环境的3D模型。 在一个实施例中，当相机跟踪失败时，检测到该相机并且通过使用先前收集的关键帧或以其它方式来重新定位相机。 在一个实施例中，通过将当前深度图与3D模型的特征实时比较，检测到环路闭合，其中移动摄像机重新访问位置。 在实施例中，检测到的环路闭合用于改善环境的3D模型的一致性和准确性。
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公开(公告)号：US20090080036A1
公开(公告)日：2009-03-26
申请号：US12299349
申请日：2007-05-03
IPC分类号： H04N1/04
CPC分类号： G01B11/2518 , G06K9/2036 , G06K9/4661
摘要： A scanner system and corresponding method, the system comprising: a scanner device (1); a target 17) and a processor (21). The scanner device (1) comprises: an emitter (13) for projecting patterned light and a sensor (12) for capturing images of the object (19). The target (17) has predetermined features visible to the sensor simultaneously with the object for enabling the processor to determine the location of the sensor with respect to the object. The generates a three-dimensional model of the object on the basis of images of the object with the patterned light projected thereon. The scanner device further comprises a light source (14) for directionally illuminating the object (19), and the sensor (12) is arranged to capture images of the illuminated object. The processor generates sets of photometric data for the object when illuminated from different directions. The processor combines the geometric data and photometric data to output a model comprising geometric information on the object together with photometric information spatially registered with the geometric information.
摘要翻译： 一种扫描仪系统和相应的方法，所述系统包括：扫描仪装置（1）; 目标17）和处理器（21）。 扫描仪装置（1）包括：用于投射图案光的发射器（13）和用于捕获物体（19）的图像的传感器（12）。 目标（17）具有与物体同时可见的预定特征，使得处理器能够确定传感器相对于物体的位置。 基于投影在其上的图案光的对象的图像，生成对象的三维模型。 扫描器装置还包括用于定向照射物体（19）的光源（14），并且传感器（12）被布置成捕获被照射物体的图像。 当从不同方向照明时，处理器生成对象的测光数据集。 处理器组合几何数据和光度数据以输出包括物体上的几何信息的模型以及与几何信息在空间上注册的光度信息。
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公开(公告)号：US08401242B2
公开(公告)日：2013-03-19
申请号：US13017587
申请日：2011-01-31
申请人： Richard Newcombe , Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
发明人： Richard Newcombe , Shahram Izadi , David Molyneaux , Otmar Hilliges , David Kim , Jamie Daniel Joseph Shotton , Pushmeet Kohli , Andrew Fitzgibbon , Stephen Edward Hodges , David Alexander Butler
IPC分类号： G06K9/00
CPC分类号： A63F13/00 , A63F13/06 , A63F2300/1087 , A63F2300/69 , G06K9/00 , G06K9/00664 , G06T7/251 , G06T7/30 , G06T2207/10028 , G06T2207/10048 , G06T2207/30244
摘要： Real-time camera tracking using depth maps is described. In an embodiment depth map frames are captured by a mobile depth camera at over 20 frames per second and used to dynamically update in real-time a set of registration parameters which specify how the mobile depth camera has moved. In examples the real-time camera tracking output is used for computer game applications and robotics. In an example, an iterative closest point process is used with projective data association and a point-to-plane error metric in order to compute the updated registration parameters. In an example, a graphics processing unit (GPU) implementation is used to optimize the error metric in real-time. In some embodiments, a dense 3D model of the mobile camera environment is used.
摘要翻译： 描述使用深度图的实时相机跟踪。 在一个实施例中，深度图帧由移动深度相机以每秒20帧的速度捕获，并且用于实时动态地更新一组注册参数，这些参数指定移动深度相机已经移动。 在实例中，实时相机跟踪输出用于计算机游戏应用和机器人。 在一个例子中，迭代最近点处理与投影数据关联和点到平面误差度量一起使用，以便计算更新的注册参数。 在一个例子中，使用图形处理单元（GPU）实现来实时优化误差度量。 在一些实施例中，使用移动照相机环境的密集3D模型。
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