公开(公告)号：US20070286492A1

公开(公告)日：2007-12-13

申请号：US11638397

申请日：2006-12-14

申请人： Jung Bae Kim ,  Gengyu Ma ,  Ji Yeun Kim ,  Jiali Zhao ,  Haibing Ren

发明人： Jung Bae Kim ,  Gengyu Ma ,  Ji Yeun Kim ,  Jiali Zhao ,  Haibing Ren

IPC分类号： G06K9/46

CPC分类号： G06K9/6209

摘要： A method of extracting a certain area from a digital image, the method including: combining image information and shape information based on an input image and prior shape information; and extracting a certain area from the input image by using the image information.

摘要翻译： 一种从数字图像提取特定区域的方法，所述方法包括：基于输入图像和先前形状信息来合成图像信息和形状信息; 以及通过使用图像信息从输入图像提取特定区域。

公开(公告)号：US07715659B2

公开(公告)日：2010-05-11

申请号：US10893346

申请日：2004-07-19

申请人： Jiali Zhao ,  Dejun Wang ,  Haibing Ren ,  Seokcheol Kee

发明人： Jiali Zhao ,  Dejun Wang ,  Haibing Ren ,  Seokcheol Kee

IPC分类号： G06K9/54

CPC分类号： G06K9/00248 ,  G06K9/00288

摘要： An apparatus for and method of performing a most informative feature extraction (MIFE) method in which a facial image is separated into sub-regions, and each sub-region makes individual contribution for performing facial recognition. Specifically, each sub-region is subjected to a sub-region based adaptive gamma (SadaGamma) correction or sub-region based histogram equalization (SHE) in order to account for different illuminations and expressions. A set of reference images is also divided into sub-regions and subjected to the SadaGamma correction or SHE. A comparison is made between the each corrected sub-region and each corresponding sub-region of the reference images. Based upon the comparisons made individually for the sub-regions of the facial image, one of the stored reference images having the greatest correspondence is chosen. While usable individually, using the MIFE and/or SadaGamma correction or SHE together achieves a lower error ratio in face recognition under different expressions, illuminations and occlusions.

摘要翻译： 一种用于执行其中将面部图像分成子区域的最具信息特征提取（MIFE）方法的装置和方法，并且每个子区域对进行面部识别作出个人贡献。 具体地说，为了解决不同的照明和表达，每个子区域经历基于子区域的自适应伽马（SadaGamma）校正或基于子区域的直方图均衡（SHE）。 一组参考图像也被划分成子区域并进行SadaGamma校正或SHE。 在每个校正子区域和参考图像的每个相应子区域之间进行比较。 基于针对面部图像的子区域的单独比较，选择具有最大对应关系的所存储的参考图像之一。 虽然可以单独使用，但使用MIFE和/或SadaGamma校正或SHE一起可以在不同表达，照明和遮挡下的脸部识别中实现较低的误差比。

公开(公告)号：US07711181B2

公开(公告)日：2010-05-04

申请号：US11168346

申请日：2005-06-29

申请人： Seokcheol Kee ,  Haibing Ren ,  Jiali Zhao

发明人： Seokcheol Kee ,  Haibing Ren ,  Jiali Zhao

IPC分类号： G06K9/00

CPC分类号： G06K9/00288 ,  G06K9/00201 ,  G06K9/20 ,  G06K2209/40 ,  G06T7/593

摘要： There is provided a method of estimating disparity for 3D object recognition. The method includes obtaining a plurality of images having different resolutions for the stereo image, estimating a disparity map for a lowest-resolution level image, estimating a coarse disparity map for an upper resolution level image by using the disparity, obtaining a fine disparity map for the upper resolution level image by using the coarse disparity, and outputting the fine disparity map as a final disparity map for the stereo image if the upper resolution level image has a resolution of a highest level.

摘要翻译： 提供了一种估计3D物体识别差异的方法。 该方法包括：获取对于立体图像具有不同分辨率的多个图像，估计最低分辨率水平图像的视差图，通过使用视差来估计上分辨率水平图像的粗视差图，获得精细视差图， 通过使用粗略视差来分辨高分辨率级别图像，并且如果高分辨率级别图像具有最高级别的分辨率，则将精细视差图输出作为立体图像的最终视差图。

公开(公告)号：US20060013509A1

公开(公告)日：2006-01-19

申请号：US11168346

申请日：2005-06-29

申请人： Seokcheol Kee ,  Haibing Ren ,  Jiali Zhao

发明人： Seokcheol Kee ,  Haibing Ren ,  Jiali Zhao

IPC分类号： G06K9/20

CPC分类号： G06K9/00288 ,  G06K9/00201 ,  G06K9/20 ,  G06K2209/40 ,  G06T7/593

摘要： There is provided a method of estimating disparity for 3D object recognition. The method includes obtaining a plurality of images having different resolutions for the stereo image, estimating a disparity map for a lowest-resolution level image, estimating a coarse disparity map for an upper resolution level image by using the disparity, obtaining a fine disparity map for the upper resolution level image by using the coarse disparity, and outputting the fine disparity map as a final disparity map for the stereo image if the upper resolution level image has a resolution of a highest level.

摘要翻译： 提供了一种估计3D对象识别差异的方法。 该方法包括：获取对于立体图像具有不同分辨率的多个图像，估计最低分辨率水平图像的视差图，通过使用视差来估计上分辨率水平图像的粗视差图，获得精细视差图， 通过使用粗略视差来分辨高分辨率级别图像，并且如果高分辨率级别图像具有最高级别的分辨率，则将精细视差图输出作为立体图像的最终视差图。

公开(公告)号：US08219571B2

公开(公告)日：2012-07-10

申请号：US11708558

申请日：2007-02-21

申请人： Haibing Ren ,  Seok-cheol Kee ,  Haitao Wang ,  Jiali Zhao

发明人： Haibing Ren ,  Seok-cheol Kee ,  Haitao Wang ,  Jiali Zhao

IPC分类号： G06F17/30

CPC分类号： G06F17/30271 ,  G06K9/6292

摘要： Provided are an object verification apparatus and method. The object verification apparatus includes a matching unit performing a plurality of different matching algorithms on a query image and generating a plurality of scores; a score normalization unit normalizing each of the generated scores to be adaptive to the query image; a weight estimation unit estimating weights of the normalized scores based on the respective matching algorithms applied; and a score fusion unit fusing the normalized scores by respectively applying the weights estimated by the weight estimation unit to the normalized scores.

摘要翻译： 提供了一种对象验证装置和方法。 对象验证装置包括对查询图像执行多个不同匹配算法并生成多个分数的匹配单元; 将所生成的分数的每一个标准化为适应于所述查询图像的分数归一化单元; 权重估计单元，基于所应用的各个匹配算法估计归一化分数的权重; 以及分数融合单元，通过将由所述权重估计单元估计的权重分别应用于所述归一化分数来使所述归一化分数融合。

公开(公告)号：US07558763B2

公开(公告)日：2009-07-07

申请号：US11454913

申请日：2006-06-19

申请人： Jiali Zhao ,  Seokcheol Kee ,  Haitao Wang ,  Haibing Ren ,  Wonjun Hwang

发明人： Jiali Zhao ,  Seokcheol Kee ,  Haitao Wang ,  Haibing Ren ,  Wonjun Hwang

IPC分类号： G06F15/18

CPC分类号： G06K9/00281 ,  G06K9/00275 ,  G06K2009/4666

摘要： A image verification method, medium, and apparatus using a local binary pattern (LBP) discriminant technique. The verification method includes generating a kernel fisher discriminant analysis (KFDA) basis vector by using the LBP feature of an input image, obtaining a Chi square inner product by using the LBP feature of an image registered in advance and a kernel LBP feature and projecting to a KFDA basis vector, obtaining a Chi square inner product by using the LBP feature of a query image and a kernel LBP feature and projecting to a KFDA basis vector, and obtaining the similarity degree of the target image and the query image that are obtained as Chi square inner product results, and projected to the KFDA basis vector. According to the method, medium, and apparatus, the KFDA based LBP shows superior performance over conventional LBP, KFDA, and biometric experimentation environment (BEE) baseline algorithms.

摘要翻译： 一种使用局部二值模式（LBP）判别技术的图像验证方法，介质和装置。 验证方法包括通过使用输入图像的LBP特征来生成内核渔夫判别分析（KFDA）基向量，通过使用预先登记的图像的LBP特征和核LBP特征来获得奇方内积，并且投影到 KFDA基矢量，通过使用查询图像的LBP特征和内核LBP特征获得奇方内积，并且投影到KFDA基向量，并且获得被获得的目标图像和查询图像的相似度 Chi Square内部产品成果，并预计以KFDA为基础。 根据该方法，介质和装置，基于KFDA的LBP显示出优于常规LBP，KFDA和生物测定实验环境（BEE）基线算法的性能。

公开(公告)号：US20070203904A1

公开(公告)日：2007-08-30

申请号：US11708558

申请日：2007-02-21

申请人： Haibing Ren ,  Seok-cheol Kee ,  Haitao Wang ,  Jiali Zhao

发明人： Haibing Ren ,  Seok-cheol Kee ,  Haitao Wang ,  Jiali Zhao

IPC分类号： G06F17/30

CPC分类号： G06F17/30271 ,  G06K9/6292

摘要： Provided are an object verification apparatus and method. The object verification apparatus includes a matching unit performing a plurality of different matching algorithms on a query image and generating a plurality of scores; a score normalization unit normalizing each of the generated scores to be adaptive to the query image; a weight estimation unit estimating weights of the normalized scores based on the respective matching algorithms applied; and a score fusion unit fusing the normalized scores by respectively applying the weights estimated by the weight estimation unit to the normalized scores.

摘要翻译： 提供了一种对象验证装置和方法。 对象验证装置包括对查询图像执行多个不同匹配算法并生成多个分数的匹配单元; 将所生成的分数的每一个标准化为适应于所述查询图像的分数归一化单元; 权重估计单元，基于所应用的各个匹配算法估计归一化分数的权重; 以及分数融合单元，通过将由所述权重估计单元估计的权重分别应用于所述归一化分数来使所述归一化分数融合。

公开(公告)号：US20070112699A1

公开(公告)日：2007-05-17

申请号：US11454913

申请日：2006-06-19

申请人： Jiali Zhao ,  Seokcheol Kee ,  Haitao Wang ,  Haibing Ren ,  Wonjun Hwang

发明人： Jiali Zhao ,  Seokcheol Kee ,  Haitao Wang ,  Haibing Ren ,  Wonjun Hwang

IPC分类号： G06F15/18

CPC分类号： G06K9/00281 ,  G06K9/00275 ,  G06K2009/4666

摘要： A image verification method, medium, and apparatus using a local binary pattern (LBP) discriminant technique. The verification method includes generating a kernel fisher discriminant analysis (KFDA) basis vector by using the LBP feature of an input image, obtaining a Chi square inner product by using the LBP feature of an image registered in advance and a kernel LBP feature and projecting to a KFDA basis vector, obtaining a Chi square inner product by using the LBP feature of a query image and a kernel LBP feature and projecting to a KFDA basis vector, and obtaining the similarity degree of the target image and the query image that are obtained as Chi square inner product results, and projected to the KFDA basis vector. According to the method, medium, and apparatus, the KFDA based LBP shows superior performance over conventional LBP, KFDA, and biometric experimentation environment (BEE) baseline algorithms.

摘要翻译： 一种使用局部二值模式（LBP）判别技术的图像验证方法，介质和装置。 验证方法包括通过使用输入图像的LBP特征来生成内核渔夫判别分析（KFDA）基向量，通过使用预先登记的图像的LBP特征和核LBP特征来获得奇方内积，并且投影到 KFDA基矢量，通过使用查询图像的LBP特征和内核LBP特征获得奇方内积，并且投影到KFDA基向量，并且获得被获得的目标图像和查询图像的相似度 Chi Square内部产品成果，并预计以KFDA为基础。 根据该方法，介质和装置，基于KFDA的LBP显示出优于常规LBP，KFDA和生物测定实验环境（BEE）基线算法的性能。

公开(公告)号：US20060285769A1

公开(公告)日：2006-12-21

申请号：US11455772

申请日：2006-06-20

申请人： Haitao Wang ,  Seokcheol Kee ,  Jiali Zhao ,  Haibing Ren

发明人： Haitao Wang ,  Seokcheol Kee ,  Jiali Zhao ,  Haibing Ren

IPC分类号： G06K9/40

CPC分类号： G06K9/00241 ,  G06T5/008 ,  G06T5/20 ,  G06T5/50 ,  G06T7/13

摘要： A method, apparatus, and medium for removing shading of an image are provided. The method of removing shading of an image includes: smoothing an input image; performing a gradient operation for the input image; performing normalization using the smoothed image and the images for which the gradient operation is performed; and integrating the normalized images. The apparatus for removing shading of an image includes: a smoothing unit smoothing an input image using a predetermined smoothing kernel; a gradient operation unit performing a gradient operation for the input image using a predetermined gradient operator; a normalization unit performing normalization using the smoothed image and the images for which the gradient operation is performed; and an image integration unit integrating the normalized images. According to the method, apparatus, and medium, by defining a face image model analysis and intrinsic and extrinsic factors and setting up a rational assumption, an integral normalized gradient image not sensitive to illumination is provided. Also, by employing an anisotropic diffusion method, a moire phenomenon in an edge region of an image can be avoided.

摘要翻译： 提供了用于去除图像的阴影的方法，装置和介质。 去除图像的阴影的方法包括：平滑输入图像; 对所述输入图像执行梯度操作; 使用平滑化图像和执行梯度操作的图像来执行归一化; 并整合归一化图像。 用于去除图像的阴影的装置包括：平滑单元，使用预定的平滑核平滑输入图像; 梯度操作单元，使用预定的梯度算子对所述输入图像执行梯度操作; 归一化单元，其使用所述平滑图像和执行了所述梯度操作的图像来执行归一化; 以及整合归一化图像的图像积分单元。 根据该方法，装置和介质，通过定义面部图像模型分析和内在和外在因素并建立合理假设，提供了对照明不敏感的积分归一化梯度图像。 此外，通过使用各向异性扩散法，可以避免图像边缘区域中的莫尔条纹现象。

公开(公告)号：US20060008150A1

公开(公告)日：2006-01-12

申请号：US10893346

申请日：2004-07-19

申请人： Jiali Zhao ,  Dejun Wang ,  Haibing Ren ,  Seokcheol Kee

发明人： Jiali Zhao ,  Dejun Wang ,  Haibing Ren ,  Seokcheol Kee

IPC分类号： G06K9/46 ,  G06K9/00

CPC分类号： G06K9/00248 ,  G06K9/00288

摘要： An apparatus for and method of performing a most informative feature extraction (MIFE) method in which a facial image is separated into sub-regions, and each sub-region makes individual contribution for performing facial recognition. Specifically, each sub-region is subjected to a sub-region based adaptive gamma (SadaGamma) correction or sub-region based histogram equalization (SHE) in order to account for different illuminations and expressions. A set of reference images is also divided into sub-regions and subjected to the SadaGamma correction or SHE. A comparison is made between the each corrected sub-region and each corresponding sub-region of the reference images. Based upon the comparisons made individually for the sub-regions of the facial image, one of the stored reference images having the greatest correspondence is chosen. While usable individually, using the MIFE and/or SadaGamma correction or SHE together achieves a lower error ratio in face recognition under different expressions, illuminations and occlusions.

摘要翻译： 一种用于执行其中将面部图像分成子区域的最具信息特征提取（MIFE）方法的装置和方法，并且每个子区域对进行面部识别作出个人贡献。 具体地说，为了解决不同的照明和表达，每个子区域经受基于子区域的自适应伽马（SadaGamma）校正或基于子区域的直方图均衡（SHE）。 一组参考图像也被划分成子区域并进行SadaGamma校正或SHE。 在每个校正子区域和参考图像的每个相应子区域之间进行比较。 基于针对面部图像的子区域的单独比较，选择具有最大对应关系的所存储的参考图像之一。 虽然可以单独使用，但使用MIFE和/或SadaGamma校正或SHE一起可以在不同表达，照明和遮挡下的脸部识别中实现较低的误差比。