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1. 发明申请

US20080166026A1 Method and apparatus for generating face descriptor using extended local binary patterns, and method and apparatus for face recognition using extended local binary patterns 审中-公开
标题翻译：使用扩展局部二进制模式生成面部描述符的方法和装置，以及使用扩展局部二进制模式进行面部识别的方法和装置
公开(公告)号：US20080166026A1
公开(公告)日：2008-07-10
申请号：US11882442
申请日：2007-08-01
申请人： Xiangsheng Huang , Won-jun Hwang , Jiali Zhao , Young-su Moon , Gyu-tae Park
发明人： Xiangsheng Huang , Won-jun Hwang , Jiali Zhao , Young-su Moon , Gyu-tae Park
IPC分类号： G06K9/00
CPC分类号： G06K9/00281
摘要： A face descriptor generating method and apparatus and face recognition method and apparatus using extended local binary pattern (LBP) are provided.Since LBP features are selected by performing a supervised learning process on the extended LBP features and the selected extended LBP features are used in face recognition, it is possible to reduce errors in face recognition or identity verification and to increase face recognition efficiency. In addition, the extended LBP features are used so that it is possible to overcome the problem of time-consumption of the process.
摘要翻译：提供了使用扩展局部二进制模式（LBP）的面部描述符生成方法和装置以及面部识别方法和装置。由于通过对扩展的LBP特征执行监督学习处理来选择LBP特征，并且所选择的扩展LBP特征用于人脸识别，可以减少面部识别或身份验证中的错误并增加面部识别效率。此外，使用扩展的LBP特征，使得可以克服该过程的时间消耗的问题。

2. 发明申请

US20080107311A1 Method and apparatus for face recognition using extended gabor wavelet features 审中-公开
标题翻译：使用扩展gabor小波特征进行人脸识别的方法和装置
公开(公告)号：US20080107311A1
公开(公告)日：2008-05-08
申请号：US11797886
申请日：2007-05-08
申请人： Xiangsheng Huang , Won-jun Hwang , Seok-chaol Kee , Young-su Moon , Gyu-lee Park , Jong-ho Lee
发明人： Xiangsheng Huang , Won-jun Hwang , Seok-chaol Kee , Young-su Moon , Gyu-lee Park , Jong-ho Lee
IPC分类号： G06K9/00
CPC分类号： G06K9/00288
摘要： A face recognition method and apparatus using extended Gabor wavelet features are provided. In the face recognition method, extended Gabor wavelet features are extracted from a face image by applying an extended Gabor wavelet filter, a Gabor wavelet feature set is selected by performing a supervised learning process on the extended Gabor wavelet features, and the selected Gabor wavelet feature set is used for face recognition. Accordingly, it is possible to solve problems of a high error rate of face recognition and low face recognition efficiency caused from a limitation of parameters of the Gabor wavelet filter. In addition, it is possible to solve the problem of increased calculation complexity caused from using an extended Gabor wavelet filter and to implement robust face recognition which is excellent in dealing with a change in expression and illumination.
摘要翻译：提供了使用扩展Gabor小波特征的人脸识别方法和装置。在面部识别方法中，通过应用扩展Gabor小波滤波器从面部图像中提取扩展Gabor小波特征，通过对扩展Gabor小波特征执行监督学习过程，选择Gabor小波特征集，并选择Gabor小波特征集合用于人脸识别。因此，可以解决由Gabor小波滤波器的参数的限制引起的面部识别的高错误率和低的脸部识别效率的问题。另外，可以解决使用扩展Gabor小波滤波器引起的增加的计算复杂度的问题，并且能够实现在处理表达和照明变化方面非常出色的鲁棒的面部识别。

3. 发明申请

US20090028444A1 Method, medium, and apparatus with object descriptor generation using curvature gabor filter 审中-公开
标题翻译：使用曲率加布尔滤波器的方法，介质和具有对象描述符生成的装置
公开(公告)号：US20090028444A1
公开(公告)日：2009-01-29
申请号：US12002764
申请日：2007-12-19
申请人： Won-Jun Hwang , Xiangsheng Huang , Seok-cheol Kee
发明人： Won-Jun Hwang , Xiangsheng Huang , Seok-cheol Kee
IPC分类号： G06K9/62
CPC分类号： G06K9/00281 , G06K9/4619 , G06K9/6256
摘要： A method, medium, and apparatus with a generated object descriptor using a curvature gabor filter, with complementary object recognition being performed by applying a general gabor filter and a curvature gabor filter having various curvatures, such that the dimension and efficiency of a feature vector can be increased by detecting correlations between features of an object searching for a parameter and its position of an optimal curvature gabor filter through boosting learning, and projecting the extracted features onto a base vector having the highest classification rate.
摘要翻译：具有使用曲率加布滤波器的生成的对象描述符的方法，介质和装置，通过应用具有各种曲率的通用格子滤波器和曲率加布滤波器来执行互补对象识别，使得特征向量的尺寸和效率可以通过检测通过增强学习来搜索参数的对象的特征与最佳曲率加布尔滤波器的位置之间的相关性，并将提取的特征投影到具有最高分类率的基本矢量上来增加。

4. 发明授权

US08803950B2 Three-dimensional face capturing apparatus and method and computer-readable medium thereof 有权
标题翻译：三维人脸捕捉装置及其计算机可读介质
公开(公告)号：US08803950B2
公开(公告)日：2014-08-12
申请号：US12862293
申请日：2010-08-24
申请人： Haibing Ren , Xiangsheng Huang , Hwa Sup Lim
发明人： Haibing Ren , Xiangsheng Huang , Hwa Sup Lim
IPC分类号： G06T15/00 , G06T17/00 , H04N5/232
CPC分类号： H04N5/23219 , G06T5/002 , G06T7/344 , G06T15/00 , G06T17/00 , G06T2200/08 , G06T2207/10024 , G06T2207/10028 , G06T2207/30201
摘要： Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.
摘要翻译：公开了一种3D人脸捕获装置，方法和计算机可读介质。作为示例，3D面部拍摄方法包括获得脸部彩色图像，获得脸部深度图像，通过计算机对准脸部彩色图像和脸部深度图像，由计算机获得2D面部3D模型模拟脸部彩色图像并覆盖由图像对准模块输出的图像上的建模2D面部区域，由计算机移除3D脸部模型的深度噪声，以及由计算机通过对准获得准确的3D面部模型 3D面部模型和3D脸部模板，并且基于3D面部模型和3D面部模板之间的配准来去除残余噪声。

5. 发明申请

US20090180671A1 Multi-view face recognition method and system 有权
标题翻译：多视角人脸识别方法及系统
公开(公告)号：US20090180671A1
公开(公告)日：2009-07-16
申请号：US12289071
申请日：2008-10-20
申请人： Jongha Lee , Xiangsheng Huang , Junghae Kim , Seong-deok Lee
发明人： Jongha Lee , Xiangsheng Huang , Junghae Kim , Seong-deok Lee
IPC分类号： G06K9/00
CPC分类号： G06K9/00275 , G06K9/6234
摘要： A multi-view face recognition method and system are provided. In the multi-view face recognition method, two images to be recognized are input, a linear projection matrix is calculated based on grouped images in a training set, two feature vectors corresponding to the two input images are extracted based on the linear projection matrix, a distance between the two extracted feature vectors is calculated, and it is determined based on the distance between the two feature vectors whether the two input images belong to a same person.
摘要翻译：提供了多视角人脸识别方法和系统。在多视图人脸识别方法中，输入要识别的两个图像，基于训练集中的分组图像计算线性投影矩阵，基于线性投影矩阵提取与两个输入图像相对应的两个特征向量，计算两个提取的特征向量之间的距离，并且基于两个特征向量之间的距离确定两个输入图像是否属于同一个人。

6. 发明申请

US20060146062A1 Method and apparatus for constructing classifiers based on face texture information and method and apparatus for recognizing face using statistical features of face texture information 审中-公开
标题翻译：基于面部纹理信息构造分类器的方法和装置以及使用面部纹理信息的统计特征来识别脸部的方法和装置
公开(公告)号：US20060146062A1
公开(公告)日：2006-07-06
申请号：US11320672
申请日：2005-12-30
申请人： Seokcheol Kee , Bin Xu , Yangsheng Wang , Ziqing Li , Xiangsheng Huang , Xiaouxu Zhou
发明人： Seokcheol Kee , Bin Xu , Yangsheng Wang , Ziqing Li , Xiangsheng Huang , Xiaouxu Zhou
IPC分类号： G09G5/00
CPC分类号： G06K9/00275 , G06K9/6212
摘要： A method and an apparatus for constructing classifiers based on face texture information and a method and an apparatus for recognizing a face using statistical features of texture information. The method of constructing classifiers based on face texture information includes: cropping a first face image and a second face image from two different images; dividing the first face image and the second face image into partial images of predetermined sizes and cropping first partial images corresponding to the first image and second partial images corresponding to the second image; extracting first texture information corresponding to texture information of each of the first partial images and second texture information corresponding to texture information of each of the second partial images; checking similarities between the texture information of partial images of the first face image and that of the corresponding partial images of the second face image; and constructing weak classifiers for recognizing an identity of the face based on partial images according to the checked similarities.
摘要翻译：一种基于面部纹理信息构建分类器的方法和装置，以及使用纹理信息的统计特征来识别面部的方法和装置。基于面部纹理信息构建分类器的方法包括：从两个不同的图像裁剪第一个面部图像和第二个面部图像; 将所述第一面部图像和所述第二面部图像分割成预定尺寸的部分图像，并且对应于所述第一图像的裁剪第一部分图像和对应于所述第二图像的所述第二部分图像; 提取与所述第一部分图像中的每一个的纹理信息相对应的第一纹理信息和对应于每个第二部分图像的纹理信息的第二纹理信息; 检查第一面部图像的部分图像的纹理信息与第二面部图像的相应部分图像的纹理信息之间的相似度; 以及构建弱分类器，用于根据所检查的相似度，基于部分图像来识别面部的身份。

7. 发明申请

US20110043610A1 THREE-DIMENSIONAL FACE CAPTURING APPARATUS AND METHOD AND COMPUTER-READABLE MEDIUM THEREOF 有权
标题翻译：三维面积测量装置及其计算机可读介质
公开(公告)号：US20110043610A1
公开(公告)日：2011-02-24
申请号：US12862293
申请日：2010-08-24
申请人： Haibing REN , Xiangsheng Huang , Hwa Sup Lim
发明人： Haibing REN , Xiangsheng Huang , Hwa Sup Lim
IPC分类号： H04N13/02 , G06K9/00
CPC分类号： H04N5/23219 , G06T5/002 , G06T7/344 , G06T15/00 , G06T17/00 , G06T2200/08 , G06T2207/10024 , G06T2207/10028 , G06T2207/30201
摘要： Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.
摘要翻译：公开了一种3D人脸捕获装置，方法和计算机可读介质。作为示例，3D面部拍摄方法包括获得脸部彩色图像，获得脸部深度图像，通过计算机对准脸部彩色图像和脸部深度图像，由计算机获得2D面部3D模型模拟脸部彩色图像并覆盖由图像对准模块输出的图像上的建模2D面部区域，由计算机移除3D脸部模型的深度噪声，以及由计算机通过对准获得准确的3D面部模型 3D面部模型和3D脸部模板，并且基于3D面部模型和3D面部模板之间的配准来去除残余噪声。

8. 发明授权

US08615113B2 Multi-view face recognition method and system 有权
公开(公告)号：US08615113B2
公开(公告)日：2013-12-24
申请号：US12289071
申请日：2008-10-20
申请人： Jongha Lee , Xiangsheng Huang , Jungbae Kim , Seong-deok Lee
发明人： Jongha Lee , Xiangsheng Huang , Jungbae Kim , Seong-deok Lee
IPC分类号： G06K9/00
CPC分类号： G06K9/00275 , G06K9/6234
摘要： A multi-view face recognition method and system are provided. In the multi-view face recognition method, two images to be recognized are input, a linear projection matrix is calculated based on grouped images in a training set, two feature vectors corresponding to the two input images are extracted based on the linear projection matrix, a distance between the two extracted feature vectors is calculated, and it is determined based on the distance between the two feature vectors whether the two input images belong to a same person.

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