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21. 发明申请

US20130010079A1 CALIBRATION BETWEEN DEPTH AND COLOR SENSORS FOR DEPTH CAMERAS 有权
标题翻译：深度摄影机的深度和颜色传感器之间的校准
公开(公告)号：US20130010079A1
公开(公告)日：2013-01-10
申请号：US13178494
申请日：2011-07-08
申请人： Cha Zhang , Zhengyou Zhang
发明人： Cha Zhang , Zhengyou Zhang
IPC分类号： H04N13/02
CPC分类号： H04N13/246 , G06T7/85 , H04N13/20 , H04N13/207 , H04N13/25 , H04N13/257 , H04N13/271
摘要： A system described herein includes a receiver component that receives a first digital image from a color camera, wherein the first digital image comprises a planar object, and a second digital image from a depth sensor, wherein the second digital image comprises the planar object. The system also includes a calibrator component that jointly calibrates the color camera and the depth sensor based at least in part upon the first digital image and the second digital image.
摘要翻译：本文描述的系统包括从彩色摄像机接收第一数字图像的接收器组件，其中第一数字图像包括平面物体和来自深度传感器的第二数字图像，其中第二数字图像包括平面物体。该系统还包括校准器组件，其至少部分地基于第一数字图像和第二数字图像来共同校准彩色摄像机和深度传感器。

22. 发明授权

US09536046B2 Automated acquisition of facial images 有权
标题翻译：自动采集面部图像
公开(公告)号：US09536046B2
公开(公告)日：2017-01-03
申请号：US12685686
申请日：2010-01-12
申请人： Michael Gillam , John Christopher Gillotte , Craig Frederick Feied , Jonathan Alan Handler , Renato Reder Cazangi , Rajesh Kutpadi Hegde , Zhengyou Zhang , Cha Zhang
发明人： Michael Gillam , John Christopher Gillotte , Craig Frederick Feied , Jonathan Alan Handler , Renato Reder Cazangi , Rajesh Kutpadi Hegde , Zhengyou Zhang , Cha Zhang
IPC分类号： G06K9/00 , G06K15/02 , G06F19/00 , G07C9/00
CPC分类号： G06F19/322 , G06F19/00 , G07C9/00079 , G07C9/00103 , G16H10/60
摘要： Described is a technology by which medical patient facial images are acquired and maintained for associating with a patient's records and/or other items. A video camera may provide video frames, such as captured when a patient is being admitted to a hospital. Face detection may be employed to clip the facial part from the frame. Multiple images of a patient's face may be displayed on a user interface to allow selection of a representative image. Also described is obtaining the patient images by processing electronic documents (e.g., patient records) to look for a face pictured therein.
摘要翻译：描述了获取和维护医疗患者面部图像以与患者的记录和/或其他项目相关联的技术。视频摄像机可以提供视频帧，例如当病人进入医院时被捕获的视频帧。可以采用脸部检测来将脸部部分从框架夹紧。可以在用户界面上显示患者脸部的多个图像，以允许选择代表性图像。还描述了通过处理电子文档（例如病人记录）来寻找其中所描绘的脸部来获得患者图像。

23. 发明申请

US20090263010A1 ADAPTING A PARAMETERIZED CLASSIFIER TO AN ENVIRONMENT 审中-公开
标题翻译：将参数化分类器适应环境
公开(公告)号：US20090263010A1
公开(公告)日：2009-10-22
申请号：US12105275
申请日：2008-04-18
申请人： Cha Zhang , Zhengyou Zhang
发明人： Cha Zhang , Zhengyou Zhang
IPC分类号： G06F15/18 , G06K9/62
CPC分类号： G06K9/6277 , G06K9/6256 , G06N20/00
摘要： A classifier is trained on a first set of examples, and the trained classifier is adapted to perform on a second set of examples. The classifier implements a parameterized labeling function. Initial training of the classifier optimizes the labeling function's parameters to minimize a cost function. The classifier and its parameters are provided to an environment in which it will operate, along with an approximation function that approximates the cost function using a compact representation of the first set of examples in place of the actual first set. A second set of examples is collected, and the parameters are modified to minimize a combined cost of labeling the first and second sets of examples. The part of the combined cost that represents the cost of the modified parameters applied to the first set is calculated using the approximation function.
摘要翻译：在第一组示例上训练分类器，并且训练分类器适于在第二组示例上执行。分类器实现参数化标签功能。分类器的初始训练优化了标签函数的参数，以最小化成本函数。分类器及其参数被提供给其将被操作的环境，以及使用第一组示例的紧凑表示代替实际的第一组近似成本函数的近似函数。收集第二组示例，并修改参数以最小化标记第一组和第二组示例的组合成本。使用近似函数计算代表施加到第一组的修改参数的成本的组合成本的部分。

24. 发明授权

US09270974B2 Calibration between depth and color sensors for depth cameras 有权
标题翻译：用于深度相机的深度和颜色传感器之间的校准
公开(公告)号：US09270974B2
公开(公告)日：2016-02-23
申请号：US13178494
申请日：2011-07-08
申请人： Cha Zhang , Zhengyou Zhang
发明人： Cha Zhang , Zhengyou Zhang
IPC分类号： H04N13/02 , G06T7/00 , H04N13/00
CPC分类号： H04N13/246 , G06T7/85 , H04N13/20 , H04N13/207 , H04N13/25 , H04N13/257 , H04N13/271
摘要： A system described herein includes a receiver component that receives a first digital image from a color camera, wherein the first digital image comprises a planar object, and a second digital image from a depth sensor, wherein the second digital image comprises the planar object. The system also includes a calibrator component that jointly calibrates the color camera and the depth sensor based at least in part upon the first digital image and the second digital image.
摘要翻译：本文描述的系统包括从彩色摄像机接收第一数字图像的接收器组件，其中第一数字图像包括平面物体和来自深度传感器的第二数字图像，其中第二数字图像包括平面物体。该系统还包括校准器组件，其至少部分地基于第一数字图像和第二数字图像来共同校准彩色摄像机和深度传感器。

25. 发明授权

US09123144B2 Computing 3D shape parameters for face animation 有权
标题翻译：计算面部动画的3D形状参数
公开(公告)号：US09123144B2
公开(公告)日：2015-09-01
申请号：US13295009
申请日：2011-11-11
申请人： Nikolay Smolyanskiy , Christian F. Huitema , Cha Zhang , Lin Liang , Sean Eron Anderson , Zhengyou Zhang
发明人： Nikolay Smolyanskiy , Christian F. Huitema , Cha Zhang , Lin Liang , Sean Eron Anderson , Zhengyou Zhang
IPC分类号： G06K9/00 , G06T17/00 , G06T7/00
CPC分类号： G06T7/20 , G06K9/00 , G06T7/579 , G06T13/20 , G06T17/00 , G06T2200/08 , G06T2207/10012 , G06T2207/10016 , G06T2207/30201
摘要： A three-dimensional shape parameter computation system and method for computing three-dimensional human head shape parameters from two-dimensional facial feature points. A series of images containing a user's face is captured. Embodiments of the system and method deduce the 3D parameters of the user's head by examining a series of captured images of the user over time and in a variety of head poses and facial expressions, and then computing an average. An energy function is constructed over a batch of frames containing 2D face feature points obtained from the captured images, and the energy function is minimized to solve for the head shape parameters valid for the batch of frames. Head pose parameters and facial expression and animation parameters can vary over each captured image in the batch of frames. In some embodiments this minimization is performed using a modified Gauss-Newton minimization technique using a single iteration.
摘要翻译：一种用于从二维面部特征点计算三维人头形状参数的三维形状参数计算系统和方法。捕获包含用户脸部的一系列图像。系统和方法的实施例通过随时间和各种头部姿势和面部表情检查用户的一系列捕获图像，然后计算平均值来推导用户头部的3D参数。在包含从捕获图像获得的2D面部特征点的一批帧上构建能量函数，并且将能量函数最小化以解决对于批次帧有效的头部形状参数。头部姿势参数和面部表情和动画参数可以在批次帧中的每个拍摄图像上变化。在一些实施例中，使用使用单次迭代的修正的高斯 - 牛顿最小化技术来执行该最小化。

26. 发明申请

US20130121526A1 COMPUTING 3D SHAPE PARAMETERS FOR FACE ANIMATION 有权
公开(公告)号：US20130121526A1
公开(公告)日：2013-05-16
申请号：US13295009
申请日：2011-11-11
申请人： Nikolay Smolyanskiy , Christian F. Huitema , Cha Zhang , Lin Liang , Sean Eron Anderson , Zhengyou Zhang
发明人： Nikolay Smolyanskiy , Christian F. Huitema , Cha Zhang , Lin Liang , Sean Eron Anderson , Zhengyou Zhang
IPC分类号： G06K9/00
CPC分类号： G06T7/20 , G06K9/00 , G06T7/579 , G06T13/20 , G06T17/00 , G06T2200/08 , G06T2207/10012 , G06T2207/10016 , G06T2207/30201
摘要： A three-dimensional shape parameter computation system and method for computing three-dimensional human head shape parameters from two-dimensional facial feature points. A series of images containing a user's face is captured. Embodiments of the system and method deduce the 3D parameters of the user's head by examining a series of captured images of the user over time and in a variety of head poses and facial expressions, and then computing an average. An energy function is constructed over a batch of frames containing 2D face feature points obtained from the captured images, and the energy function is minimized to solve for the head shape parameters valid for the batch of frames. Head pose parameters and facial expression and animation parameters can vary over each captured image in the batch of frames. In some embodiments this minimization is performed using a modified Gauss-Newton minimization technique using a single iteration.

27. 发明申请

US20110170739A1 Automated Acquisition of Facial Images 有权
标题翻译：自动采集面部图像
公开(公告)号：US20110170739A1
公开(公告)日：2011-07-14
申请号：US12685686
申请日：2010-01-12
申请人： Michael Gillam , John Christopher Gillotte , Craig Frederick Feied , Jonathan Alan Handler , Renato Reder Cazangi , Rajesh Kutpadi Hegde , Zhengyou Zhang , Cha Zhang
发明人： Michael Gillam , John Christopher Gillotte , Craig Frederick Feied , Jonathan Alan Handler , Renato Reder Cazangi , Rajesh Kutpadi Hegde , Zhengyou Zhang , Cha Zhang
IPC分类号： G06K9/00
CPC分类号： G06F19/322 , G06F19/00 , G07C9/00079 , G07C9/00103 , G16H10/60
摘要： Described is a technology by which medical patient facial images are acquired and maintained for associating with a patient's records and/or other items. A video camera may provide video frames, such as captured when a patient is being admitted to a hospital. Face detection may be employed to clip the facial part from the frame. Multiple images of a patient's face may be displayed on a user interface to allow selection of a representative image. Also described is obtaining the patient images by processing electronic documents (e.g., patient records) to look for a face pictured therein.
摘要翻译：描述了获取和维护医疗患者面部图像以与患者的记录和/或其他项目相关联的技术。视频摄像机可以提供视频帧，例如当病人进入医院时被捕获的视频帧。可以采用脸部检测来将脸部部分从框架夹紧。可以在用户界面上显示患者脸部的多个图像，以允许选择代表性图像。还描述了通过处理电子文档（例如病人记录）来寻找其中所描绘的脸部来获得患者图像。

28. 发明申请

US20110119210A1 Multiple Category Learning for Training Classifiers 有权
标题翻译：训练分类器的多类学习
公开(公告)号：US20110119210A1
公开(公告)日：2011-05-19
申请号：US12618799
申请日：2009-11-16
申请人： Cha Zhang , Zhengyou Zhang
发明人： Cha Zhang , Zhengyou Zhang
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： Described is multiple category learning to jointly train a plurality of classifiers in an iterative manner. Each training iteration associates an adaptive label with each training example, in which during the iterations, the adaptive label of any example is able to be changed by the subsequent reclassification. In this manner, any mislabeled training example is corrected by the classifiers during training. The training may use a probabilistic multiple category boosting algorithm that maintains probability data provided by the classifiers, or a winner-take-all multiple category boosting algorithm selects the adaptive label based upon the highest probability classification. The multiple category boosting training system may be coupled to a multiple instance learning mechanism to obtain the training examples. The trained classifiers may be used as weak classifiers that provide a label used to select a deep classifier for further classification, e.g., to provide a multi-view object detector.
摘要翻译：描述了多类学习，以迭代的方式联合训练多个分类器。每个训练迭代将自适应标签与每个训练示例相关联，其中在迭代期间，任何示例的自适应标签能够由随后的重新分类改变。以这种方式，任何错误标记的训练示例在训练期间由分类器校正。训练可以使用维护由分类器提供的概率数据的概率多类别提升算法，或者获胜者全部多类别增强算法基于最高概率分类来选择自适应标签。多类别增强训练系统可以耦合到多实例学习机制以获得训练示例。经训练的分类器可以用作弱分类器，其提供用于选择用于进一步分类的深分类器的标签，例如提供多视图对象检测器。

29. 发明申请

US20100329517A1 BOOSTED FACE VERIFICATION 有权
标题翻译：增强面验证
公开(公告)号：US20100329517A1
公开(公告)日：2010-12-30
申请号：US12492417
申请日：2009-06-26
申请人： Cha Zhang , Xiaogang Wang , Zhengyou Zhang
发明人： Cha Zhang , Xiaogang Wang , Zhengyou Zhang
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06K9/6256 , G06K9/00248 , G06K9/4671 , G06K2009/4666
摘要： Techniques for face verification are described. Local binary pattern (LBP) features and boosting classifiers are used to verify faces in images. A boosted multi-task learning algorithm is used for face verification in images. Finally, boosted face verification is used to verify faces in videos.
摘要翻译：描述面部验证技术。本地二进制模式（LBP）功能和增强分类器用于验证图像中的人脸。增强的多任务学习算法被用于图像中的面部验证。最后，提升的面部验证用于验证视频中的人脸。

30. 发明申请

US20080181430A1 MULTI-SENSOR SOUND SOURCE LOCALIZATION 有权
标题翻译：多传感器声源定位
公开(公告)号：US20080181430A1
公开(公告)日：2008-07-31
申请号：US11627799
申请日：2007-01-26
申请人： Cha Zhang , Dinei Florencio , Zhengyou Zhang
发明人： Cha Zhang , Dinei Florencio , Zhengyou Zhang
IPC分类号： H04R3/00
CPC分类号： H04R1/406 , H04R3/005 , H04S2400/11
摘要： A multi-sensor sound source localization (SSL) technique is presented which provides a true maximum likelihood (ML) treatment for microphone arrays having more than one pair of audio sensors. Generally, this is accomplished by selecting a sound source location that results in a time of propagation from the sound source to the audio sensors of the array, which maximizes a likelihood of simultaneously producing audio sensor output signals inputted from all the sensors in the array. The likelihood includes a unique term that estimates an unknown audio sensor response to the source signal for each of the sensors in the array.
摘要翻译：提出了一种多传感器声源定位（SSL）技术，为具有多于一对音频传感器的麦克风阵列提供真正的最大似然（ML）处理。通常，这是通过选择导致从声源传播到阵列的音频传感器的时间的声源位置来实现的，这最大化同时产生从阵列中的所有传感器输入的音频传感器输出信号的可能性。可能性包括一个唯一的术语，它估计阵列中每个传感器对源信号的未知音频传感器响应。

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