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1. 发明授权

US08687880B2 Real time head pose estimation 有权
标题翻译：实时头部姿态估计
公开(公告)号：US08687880B2
公开(公告)日：2014-04-01
申请号：US13425188
申请日：2012-03-20
申请人： Yichen Wei , Fang Wen , Jian Sun , Tommer Leyvand , Jinyu Li , Casey Meekhof , Tim Keosababian
发明人： Yichen Wei , Fang Wen , Jian Sun , Tommer Leyvand , Jinyu Li , Casey Meekhof , Tim Keosababian
IPC分类号： G06K9/62
CPC分类号： G06K9/00281 , G06K9/00362 , G06K2009/4666
摘要： Methods are provided for generating a low dimension pose space and using the pose space to estimate one or more head rotation angles of a user head. In one example, training image frames including a test subject head are captured under a plurality of conditions. For each frame an actual head rotation angle about a rotation axis is recorded. In each frame a face image is detected and converted to an LBP feature vector. Using principal component analysis a PCA feature vector is generated. Pose classes related to rotation angles about a rotation axis are defined. The PCA feature vectors are grouped into a pose class that corresponds to the actual rotation angle associated with the PCA feature vector. Linear discriminant analysis is applied to the pose classes to generate the low dimension pose space.
摘要翻译：提供了用于产生低维度姿态空间并且使用姿态空间来估计用户头部的一个或多个头部旋转角度的方法。在一个示例中，在多个条件下捕获包括测试对象头的训练图像帧。对于每个帧，记录关于旋转轴的实际头部旋转角度。在每帧中，检测到脸部图像并将其转换为LBP特征向量。使用主成分分析生成PCA特征向量。定义与旋转轴相关的旋转角度的姿态类。 PCA特征向量被分组为与PCA特征向量相关联的实际旋转角度对应的姿态类别。将线性判别分析应用于姿态类以生成低维姿态空间。

2. 发明授权

US08660306B2 Estimated pose correction 有权
标题翻译：估计姿态矫正
公开(公告)号：US08660306B2
公开(公告)日：2014-02-25
申请号：US13424867
申请日：2012-03-20
申请人： Zhuowen Tu , Wei Shen , Ke Deng , Tommer Leyvand , Baining Guo
发明人： Zhuowen Tu , Wei Shen , Ke Deng , Tommer Leyvand , Baining Guo
IPC分类号： G06K9/00 , H04N5/225 , G01R21/00
CPC分类号： G06K9/00375 , G06K9/6297
摘要： Embodiments are disclosed that relate to the correction of an estimated pose determined from depth image data. One disclosed embodiment provides, on a computing system, a method of obtaining a representation of a pose of articulated object from image data capturing the articulated object. The method comprises receiving the depth image data, obtaining an initial estimated skeleton of the articulated object from the depth image data, applying a random forest subspace regression function to the initial estimated skeleton, and determining the representation of the pose based upon a result of applying the random forest subspace regression to the initial estimated skeleton.
摘要翻译：公开了涉及从深度图像数据确定的估计姿势的校正的实施例。一个公开的实施例在计算系统上提供了一种从捕获铰接对象的图像数据获得关节物体的姿态的表示的方法。该方法包括接收深度图像数据，从深度图像数据获得关节物体的初始估计骨架，对初始估计骨架应用随机森林子空间回归函数，以及基于应用结果确定姿势的表示随机森林子空间回归到初始估计骨架。

3. 发明申请

US20130251244A1 REAL TIME HEAD POSE ESTIMATION 有权
标题翻译：实时头枕估计
公开(公告)号：US20130251244A1
公开(公告)日：2013-09-26
申请号：US13425188
申请日：2012-03-20
申请人： Yichen Wei , Fang Wen , Jian Sun , Tommer Leyvand , Jinyu Li , Casey Meekhof , Tim Keosababian
发明人： Yichen Wei , Fang Wen , Jian Sun , Tommer Leyvand , Jinyu Li , Casey Meekhof , Tim Keosababian
IPC分类号： G06K9/68 , G06K9/62
CPC分类号： G06K9/00281 , G06K9/00362 , G06K2009/4666
摘要： Methods are provided for generating a low dimension pose space and using the pose space to estimate one or more head rotation angles of a user head. In one example, training image frames including a test subject head are captured under a plurality of conditions. For each frame an actual head rotation angle about a rotation axis is recorded. In each frame a face image is detected and converted to an LBP feature vector. Using principal component analysis a PCA feature vector is generated. Pose classes related to rotation angles about a rotation axis are defined. The PCA feature vectors are grouped into a pose class that corresponds to the actual rotation angle associated with the PCA feature vector. Linear discriminant analysis is applied to the pose classes to generate the low dimension pose space.
摘要翻译：提供了用于产生低维度姿态空间并且使用姿态空间来估计用户头部的一个或多个头部旋转角度的方法。在一个示例中，在多个条件下捕获包括测试对象头的训练图像帧。对于每个帧，记录关于旋转轴的实际头部旋转角度。在每帧中，检测到脸部图像并将其转换为LBP特征向量。使用主成分分析生成PCA特征向量。定义与旋转轴相关的旋转角度的姿态类。 PCA特征向量被分组为与PCA特征向量相关联的实际旋转角度对应的姿态类别。将线性判别分析应用于姿态类以生成低维姿态空间。

4. 发明授权

US08483436B2 Systems and methods for tracking a model 有权
标题翻译：跟踪模型的系统和方法
公开(公告)号：US08483436B2
公开(公告)日：2013-07-09
申请号：US13289823
申请日：2011-11-04
申请人： Johnny Chung Lee , Tommer Leyvand , Simon Piotr Stachniak , Craig Peeper
发明人： Johnny Chung Lee , Tommer Leyvand , Simon Piotr Stachniak , Craig Peeper
IPC分类号： G06K9/00
CPC分类号： G06K9/00624 , G06F3/017 , G06K9/00362 , G06T7/251 , G06T7/579 , G06T15/00 , G06T2200/04 , G06T2207/10016 , G06T2207/10028 , G06T2207/30196 , H04N13/20
摘要： An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A model may be adjusted based on a location or position of one or more extremities estimated or determined for a human target in the grid of voxels. The model may also be adjusted based on a default location or position of the model in a default pose such as a T-pose, a DaVinci pose, and/or a natural pose.
摘要翻译：可以由设备接收，观察或捕获诸如场景的深度图像的图像。然后可以基于深度图像生成体素的网格，使得可以对深度图像进行下采样。可以基于在体素网格中为人类目标估计或确定的一个或多个末端的位置或位置来调整模型。模型还可以基于默认位置或模型在诸如T姿势，达芬奇姿态和/或自然姿势之类的默认姿势中的位置来调整。

5. 发明授权

US08265341B2 Voice-body identity correlation 有权
标题翻译：语音身份相关性
公开(公告)号：US08265341B2
公开(公告)日：2012-09-11
申请号：US12692797
申请日：2010-01-25
申请人： Mitchell Dernis , Tommer Leyvand , Christian Klein , Jinyu Li
发明人： Mitchell Dernis , Tommer Leyvand , Christian Klein , Jinyu Li
IPC分类号： G06K9/00
CPC分类号： G06K9/00892 , A63F13/213 , A63F13/215 , A63F13/79 , G06F17/30787 , G10L17/10 , G10L2021/02166
摘要： A system and method are disclosed for tracking image and audio data over time to automatically identify a person based on a correlation of their voice with their body in a multi-user game or multimedia setting.
摘要翻译：公开了一种系统和方法，用于随着时间的推移跟踪图像和音频数据，以在多用户游戏或多媒体设置中基于他们的声音与他们的身体的相关性来自动识别人。

6. 发明申请

US20120128208A1 Human Tracking System 有权
标题翻译：人体跟踪系统
公开(公告)号：US20120128208A1
公开(公告)日：2012-05-24
申请号：US13365121
申请日：2012-02-02
申请人： Tommer Leyvand , Johnny Lee , Szymon Stachniak , Craig Peeper , Shao Liu
发明人： Tommer Leyvand , Johnny Lee , Szymon Stachniak , Craig Peeper , Shao Liu
IPC分类号： G06K9/00
CPC分类号： A63F13/52 , A63F13/06 , A63F13/10 , A63F13/213 , A63F13/428 , A63F2300/1075 , A63F2300/6045 , G06F3/017 , G06K9/00342 , G06K9/00362 , G06K9/00711 , G06K9/44 , G06K9/469 , G06T7/194 , G06T7/75 , G06T2207/10028 , G06T2207/30196
摘要： An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.
摘要翻译：可以由设备接收，观察或捕获诸如场景的深度图像的图像。然后可以基于深度图像生成体素的网格，使得可以对深度图像进行下采样。包含在体素网格中的背景也可以被去除以分离与诸如人类目标之类的前景对象相关联的一个或多个体素。可以确定孤立的人类目标的一个或多个末端的位置或位置，并且可以基于一个或多个末端的位置或位置来调整模型。

7. 发明申请

US20110184735A1 SPEECH RECOGNITION ANALYSIS VIA IDENTIFICATION INFORMATION 有权
标题翻译：通过识别信息进行语音识别分析
公开(公告)号：US20110184735A1
公开(公告)日：2011-07-28
申请号：US12692538
申请日：2010-01-22
申请人： Jason Flaks , Dax Hawkins , Christian Klein , Mitchell Stephen Dernis , Tommer Leyvand , Ali M. Vassigh , Duncan McKay
发明人： Jason Flaks , Dax Hawkins , Christian Klein , Mitchell Stephen Dernis , Tommer Leyvand , Ali M. Vassigh , Duncan McKay
IPC分类号： G10L15/00 , G10L17/00 , G10L15/04 , G10L21/00 , G06K9/00
CPC分类号： G10L15/24 , A63F2300/1081 , A63F2300/1087 , A63F2300/6072 , G06K9/0057 , G10L17/00 , G10L2015/228 , G10L2021/02166
摘要： Embodiments are disclosed that relate to the use of identity information to help avoid the occurrence of false positive speech recognition events in a speech recognition system. One embodiment provides a method comprising receiving speech recognition data comprising a recognized speech segment, acoustic locational data related to a location of origin of the recognized speech segment as determined via signals from the microphone array, and confidence data comprising a recognition confidence value, and also receiving image data comprising visual locational information related to a location of each person in an image. The acoustic locational data is compared to the visual locational data to determine whether the recognized speech segment originated from a person in the field of view of the image sensor, and the confidence data is adjusted depending on this determination.
摘要翻译：公开了涉及使用身份信息来帮助避免在语音识别系统中发生假阳性语音识别事件的实施例。一个实施例提供了一种方法，包括接收包括识别的语音段的语音识别数据，与通过来自麦克风阵列的信号确定的识别的语音段的原点的位置有关的声学位置数据，以及包括识别置信度的置信度数据，以及接收图像数据，其包括与图像中的每个人的位置相关的视觉位置信息。将声学位置数据与视觉位置数据进行比较，以确定识别的语音片段是否源于图像传感器的视野中的人，并且根据该确定来调整置信度数据。

8. 发明授权

US08866889B2 In-home depth camera calibration 有权
标题翻译：家用深度相机校准
公开(公告)号：US08866889B2
公开(公告)日：2014-10-21
申请号：US12939038
申请日：2010-11-03
申请人： Prafulla J. Masalkar , Szymon P. Stachniak , Tommer Leyvand , Zhengyou Zhang , Leonardo Del Castillo , Zsolt Mathe
发明人： Prafulla J. Masalkar , Szymon P. Stachniak , Tommer Leyvand , Zhengyou Zhang , Leonardo Del Castillo , Zsolt Mathe
IPC分类号： H04N13/02 , H04N13/00 , G06F3/01 , H04N13/04 , G06T7/00
CPC分类号： H04N13/327 , A63F13/213 , A63F13/22 , G06F3/017 , G06T7/80 , G06T2207/10021 , G06T2207/10028 , G06T2207/30196 , H04N13/128 , H04N13/271
摘要： A system and method are disclosed for calibrating a depth camera in a natural user interface. The system in general obtains an objective measurement of true distance between a capture device and one or more objects in a scene. The system then compares the true depth measurement to the depth measurement provided by the depth camera at one or more points and determines an error function describing an error in the depth camera measurement. The depth camera may then be recalibrated to correct for the error. The objective measurement of distance to one or more objects in a scene may be accomplished by a variety of systems and methods.
摘要翻译：公开了用于在自然界面中校准深度相机的系统和方法。该系统通常获得捕获装置与场景中的一个或多个物体之间的真实距离的客观测量。然后，系统将真实深度测量与深度相机在一个或多个点提供的深度测量值进行比较，并确定描述深度相机测量中的误差的误差函数。然后可以重新校准深度相机以校正错误。可以通过各种系统和方法来实现对场景中的一个或多个对象的距离的客观测量。

9. 发明授权

US08564534B2 Human tracking system 有权
公开(公告)号：US08564534B2
公开(公告)日：2013-10-22
申请号：US12575388
申请日：2009-10-07
申请人： Tommer Leyvand , Johnny Lee , Craig Peeper , Szymon Stachniak , Shao Liu
发明人： Tommer Leyvand , Johnny Lee , Craig Peeper , Szymon Stachniak , Shao Liu
IPC分类号： G09G5/00
CPC分类号： A63F13/52 , A63F13/06 , A63F13/10 , A63F13/213 , A63F13/428 , A63F2300/1075 , A63F2300/6045 , G06F3/017 , G06K9/00342 , G06K9/00362 , G06K9/00711 , G06K9/44 , G06K9/469 , G06T7/194 , G06T7/75 , G06T2207/10028 , G06T2207/30196
摘要： An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.

10. 发明授权

US08553939B2 Pose tracking pipeline 有权
公开(公告)号：US08553939B2
公开(公告)日：2013-10-08
申请号：US13408775
申请日：2012-02-29
申请人： Robert Matthew Craig , Tommer Leyvand , Craig Peeper , Momin M. Al-Ghosien , Matt Bronder , Oliver Williams , Ryan M. Geiss , Jamie Daniel Joseph Shotton , Johnny Lee , Mark Finocchio
发明人： Robert Matthew Craig , Tommer Leyvand , Craig Peeper , Momin M. Al-Ghosien , Matt Bronder , Oliver Williams , Ryan M. Geiss , Jamie Daniel Joseph Shotton , Johnny Lee , Mark Finocchio
IPC分类号： G06K9/00 , H04N11/02
CPC分类号： G06K9/00335 , A63F13/428 , A63F2300/1006 , A63F2300/1093 , G06F3/011 , G06F3/033 , G06K9/00369 , G06T17/10 , G06T19/00
摘要： A method of tracking a target includes receiving from a source a depth image of a scene including the human subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that belong to the human subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of shapes.

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