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1. 发明授权

US08027541B2 Image organization based on image content 有权
标题翻译：基于图像内容的图像组织
公开(公告)号：US08027541B2
公开(公告)日：2011-09-27
申请号：US11725129
申请日：2007-03-15
申请人： Gang Hua , Steven M. Drucker , Michael Revow , Paul A. Viola , Richard Zemel
发明人： Gang Hua , Steven M. Drucker , Michael Revow , Paul A. Viola , Richard Zemel
IPC分类号： G06K9/46
CPC分类号： G06K9/00228 , G06K9/6251
摘要： A system for organizing images includes an extraction component that extracts visual information (e.g., faces, scenes, etc.) from the images. The extracted visual information is provided to a comparison component which computes similarity confidence data between the extracted visual information. The similarity confidence data is an indication of the likelihood that items of extracted visual information are similar. The comparison component then generates a visual distribution of the extracted visual information based upon the similarity confidence data. The visual distribution can include groupings of the extracted visual information based on computed similarity confidence data. For example, the visual distribution can be a two-dimensional layout of faces organized based on the computed similarity confidence data—with faces in closer proximity faces computed to have a greater probability of representing the same person. The visual distribution can then be utilized by a user to sort, organize and/or tag images.
摘要翻译：用于组织图像的系统包括从图像中提取视觉信息（例如，面部，场景等）的提取组件。提取的视觉信息被提供给计算提取的视觉信息之间的相似性置信度数据的比较部件。相似性置信度数据是提取的视觉信息的项目相似的可能性的指示。然后，比较组件基于相似性置信度数据生成所提取的视觉信息的视觉分布。视觉分布可以包括基于计算的相似性置信度数据提取的视觉信息的分组。例如，视觉分布可以是基于所计算的相似性置信度数据组织的面部的二维布局，其中更接近的面中的面被计算为具有更大的代表同一人的概率。然后用户可以利用视觉分布来对图像进行分类，组织和/或标记。

2. 发明申请

US20080226174A1 Image Organization 有权
标题翻译：图像组织
公开(公告)号：US20080226174A1
公开(公告)日：2008-09-18
申请号：US11725129
申请日：2007-03-15
申请人： Gang Hua , Steven M. Drucker , Michael Revow , Paul A. Viola , Richard Zemel
发明人： Gang Hua , Steven M. Drucker , Michael Revow , Paul A. Viola , Richard Zemel
IPC分类号： G06K9/68 , G06K9/46
CPC分类号： G06K9/00228 , G06K9/6251
摘要： A system for organizing images includes an extraction component that extracts visual information (e.g., faces, scenes, etc.) from the images. The extracted visual information is provided to a comparison component which computes similarity confidence data between the extracted visual information. The similarity confidence data is an indication of the likelihood that items of extracted visual information are similar. The comparison component then generates a visual distribution of the extracted visual information based upon the similarity confidence data. The visual distribution can include groupings of the extracted visual information based on computed similarity confidence data. For example, the visual distribution can be a two-dimensional layout of faces organized based on the computed similarity confidence data—with faces in closer proximity faces computed to have a greater probability of representing the same person. The visual distribution can then be utilized by a user to sort, organize and/or tag images.
摘要翻译：用于组织图像的系统包括从图像中提取视觉信息（例如，面部，场景等）的提取组件。提取的视觉信息被提供给计算提取的视觉信息之间的相似性置信度数据的比较部件。相似性置信度数据是提取的视觉信息的项目相似的可能性的指示。然后，比较组件基于相似性置信度数据生成所提取的视觉信息的视觉分布。视觉分布可以包括基于计算的相似性置信度数据提取的视觉信息的分组。例如，视觉分布可以是基于所计算的相似性置信度数据组织的面部的二维布局，其中更接近的面中的面被计算为具有更大的代表同一人的概率。然后用户可以利用视觉分布来对图像进行分类，组织和/或标记。

3. 发明授权

US07936906B2 Face recognition using discriminatively trained orthogonal tensor projections 有权
标题翻译：使用区分训练正交张量投影的人脸识别
公开(公告)号：US07936906B2
公开(公告)日：2011-05-03
申请号：US11763909
申请日：2007-06-15
申请人： Gang Hua , Paul A Viola , Steven M. Drucker , Michael Revow
发明人： Gang Hua , Paul A Viola , Steven M. Drucker , Michael Revow
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/6232
摘要： Systems and methods are described for face recognition using discriminatively trained orthogonal rank one tensor projections. In an exemplary system, images are treated as tensors, rather than as conventional vectors of pixels. During runtime, the system designs visual features—embodied as tensor projections—that minimize intraclass differences between instances of the same face while maximizing interclass differences between the face and faces of different people. Tensor projections are pursued sequentially over a training set of images and take the form of a rank one tensor, i.e., the outer product of a set of vectors. An exemplary technique ensures that the tensor projections are orthogonal to one another, thereby increasing ability to generalize and discriminate image features over conventional techniques. Orthogonality among tensor projections is maintained by iteratively solving an ortho-constrained eigenvalue problem in one dimension of a tensor while solving unconstrained eigenvalue problems in additional dimensions of the tensor.
摘要翻译：使用区分训练的正交秩一张量投影描述用于人脸识别的系统和方法。在示例性系统中，图像被视为张量，而不是像传统的像素矢量。在运行期间，系统设计视觉特征 - 体现为张量投影 - 最大限度地减少不同人脸部和脸部之间的类间差异，从而最大限度地减少同一脸部实例之间的差异。张量投影在训练图像集上顺序追溯，并采取一级张量的形式，即一组向量的外积。示例性技术确保张量投影彼此正交，从而增加了与常规技术相比的概括和区分图像特征的能力。通过迭代求解张量的一维中的邻域约束特征值问题，同时解决张量的附加维度中的无约束特征值问题，维持张量投影中的正交性。

4. 发明申请

US20080310687A1 Face Recognition Using Discriminatively Trained Orthogonal Tensor Projections 有权
标题翻译：使用歧视性训练正交张量投影的人脸识别
公开(公告)号：US20080310687A1
公开(公告)日：2008-12-18
申请号：US11763909
申请日：2007-06-15
申请人： Gang Hua , Paul A. Viola , Steven M. Drucker , Michael Revow
发明人： Gang Hua , Paul A. Viola , Steven M. Drucker , Michael Revow
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/6232
摘要： Systems and methods are described for face recognition using discriminatively trained orthogonal rank one tensor projections. In an exemplary system, images are treated as tensors, rather than as conventional vectors of pixels. During runtime, the system designs visual features—embodied as tensor projections—that minimize intraclass differences between instances of the same face while maximizing interclass differences between the face and faces of different people. Tensor projections are pursued sequentially over a training set of images and take the form of a rank one tensor, i.e., the outer product of a set of vectors. An exemplary technique ensures that the tensor projections are orthogonal to one another, thereby increasing ability to generalize and discriminate image features over conventional techniques. Orthogonality among tensor projections is maintained by iteratively solving an ortho-constrained eigenvalue problem in one dimension of a tensor while solving unconstrained eigenvalue problems in additional dimensions of the tensor.
摘要翻译：使用区分训练的正交秩一张量投影描述用于人脸识别的系统和方法。在示例性系统中，图像被视为张量，而不是像传统的像素矢量。在运行期间，系统设计视觉特征 - 体现为张量投影 - 最大限度地减少不同人脸部和脸部之间的类间差异，从而最大限度地减少同一脸部实例之间的差异。张量投影在训练图像集上顺序追溯，并采取一级张量的形式，即一组向量的外积。示例性技术确保张量投影彼此正交，从而增加了与常规技术相比的概括和区分图像特征的能力。通过迭代求解张量的一维中的邻域约束特征值问题，同时解决张量的附加维度中的无约束特征值问题，维持张量投影中的正交性。

5. 发明授权

US08891861B2 Image classification 有权
标题翻译：图像分类
公开(公告)号：US08891861B2
公开(公告)日：2014-11-18
申请号：US13371719
申请日：2012-02-13
申请人： Gang Hua , Paul Viola
发明人： Gang Hua , Paul Viola
IPC分类号： G06K9/62 , G06F17/30 , G06K9/00 , G06K9/46
CPC分类号： G06F17/3025 , G06F17/30262 , G06K9/00664 , G06K9/4642 , G06K9/4652 , G06K9/6256 , G06K9/6285
摘要： Images are classified as photos (e.g., natural photographs) or graphics (e.g., cartoons, synthetically generated images), such that when searched (online) with a filter, an image database returns images corresponding to the filter criteria (e.g., either photos or graphics will be returned). A set of image statistics pertaining to various visual cues (e.g., color, texture, shape) are identified in classifying the images. These image statistics, combined with pre-tagged image metadata defining an image as either a graphic or a photo, may be used to train a boosting decision tree. The trained boosting decision tree may be used to classify additional images as graphics or photos based on image statistics determined for the additional images.
摘要翻译：图像被分类为照片（例如，自然照片）或图形（例如，漫画，综合生成的图像），使得当用过滤器搜索（在线）时，图像数据库返回与过滤标准相对应的图像（例如，照片或图形将被返回）。在对图像进行分类时，识别关于各种视觉提示（例如，颜色，纹理，形状）的一组图像统计信息。这些图像统计信息与将图像定义为图形或照片的预先标记的图像元数据可以用于训练增强决策树。经训练的增强决策树可以用于基于为附加图像确定的图像统计来将附加图像分类为图形或照片。

6. 发明授权

US08644563B2 Recognition of faces using prior behavior 有权
标题翻译：使用先前行为识别面部
公开(公告)号：US08644563B2
公开(公告)日：2014-02-04
申请号：US12637494
申请日：2009-12-14
申请人： Amir Akbarzadeh , Gang Hua
发明人： Amir Akbarzadeh , Gang Hua
IPC分类号： G06K9/00
CPC分类号： G06K9/00288 , G06K9/00677 , G06K9/6212
摘要： Face recognition may be performed using a combination of visual analysis and social context. In one example, a web site such as a social networking site or photo-sharing site allows users to upload photos, and allows faces that appear in the photo to be tagged with users' names. When user A uploads a new photo, two analyses may be performed. First, a face in the photo is compared with known faces of users to determine similarity. Second, it is determined which other users user A frequently uploads photos of. Two probability distributions are created. One distribution assigns high probabilities to users whose photos are similar to the new photo. The other assigns high probabilities to users who frequently appear in photos uploaded by user A. These probability distributions are combined, and the person in the photo is identified as being the person with the highest probability.
摘要翻译：可以使用视觉分析和社会语境的组合来执行面部识别。在一个示例中，诸如社交网站或照片共享网站的网站允许用户上传照片，并且允许照片中出现的脸部被用户的姓名标记。当用户A上传新照片时，可能会执行两次分析。首先，将照片中的脸部与用户的已知脸部进行比较，以确定相似性。其次，确定哪些其他用户A经常上传照片。创建两个概率分布。一个分配对于照片类似于新照片的用户分配高概率。另一方则将频繁出现在用户A上传的照片中的用户分配给高概率。这些概率分布相结合，照片中的人被识别为具有最高概率的人。

7. 发明申请

US20120159404A1 DETECTING VISUAL GESTURAL PATTERNS 审中-公开
标题翻译：检测视觉图案
公开(公告)号：US20120159404A1
公开(公告)日：2012-06-21
申请号：US13398645
申请日：2012-02-16
申请人： Srinath Vasireddy , Sergey Chub , Gang Hua , Ting-yi Yang
发明人： Srinath Vasireddy , Sergey Chub , Gang Hua , Ting-yi Yang
IPC分类号： G06F3/033
CPC分类号： H04N19/533 , G06T7/223 , G06T2207/10016 , H04N19/56
摘要： A processing device and method are provided for capturing images, via an image-capturing component of a processing device, and determining a motion of the processing device. An adaptive search center technique may be employed to determine a search center with respect to multiple equal-sized regions of an image frame, based on previously estimated motion vectors. One of several fast block matching methods may be used, based on one or more conditions, to match a block of pixels of one image frame with a second block of pixels of a second image. Upon matching blocks of pixels, motion vectors of the multiple equal-sized regions may be estimated. The motion may be determined, based on the estimated motion vectors, and an associated action may be performed. Various embodiments may implement techniques to distinguish motion blur from de-focus blur and to determine a change in lighting condition.
摘要翻译：提供了一种处理装置和方法，用于经由处理装置的图像捕获部件捕获图像，并且确定处理装置的运动。可以采用自适应搜索中心技术来基于先前估计的运动矢量来确定关于图像帧的多个等大小区域的搜索中心。可以使用几种快速块匹配方法中的一种，基于一个或多个条件来匹配一个图像帧的像素块与第二图像的第二像素块。在匹配像素块之后，可以估计多个等大小区域的运动矢量。可以基于估计的运动矢量来确定运动，并且可以执行相关联的动作。各种实施例可以实现将运动模糊与去焦点模糊区分开来并且确定照明条件的变化的技术。

8. 发明申请

US20100246969A1 COMPUTATIONALLY EFFICIENT LOCAL IMAGE DESCRIPTORS 审中-公开
标题翻译：计算效率高的局部图像描述符
公开(公告)号：US20100246969A1
公开(公告)日：2010-09-30
申请号：US12410469
申请日：2009-03-25
申请人： Simon A. J. Winder , Gang Hua
发明人： Simon A. J. Winder , Gang Hua
IPC分类号： G06K9/46
CPC分类号： G06K9/4671
摘要： Described is a technology in which an image (or image patch) is processed into a highly discriminative and computationally efficient image descriptor that has a low storage footprint. Feature vectors are generated from an image (or image patch), and further processed via a polar Gaussian pooling approach (a DAISY configuration) into a descriptor. The descriptor is normalized, and processed with a dimension reduction component and a quantization component (based upon dynamic range reduction) into a finalized descriptor, which may be further compressed. The resulting descriptors have significantly reduced error rates and significantly smaller sizes than other image descriptors (such as SIFT-based descriptors).
摘要翻译：描述了一种技术，其中图像（或图像贴片）被处理成具有低存储空间的高度辨别性和计算效率的图像描述符。特征向量从图像（或图像块）生成，并且通过极高斯混合方法（DAISY配置）进一步处理成描述符。描述符被归一化，并且将尺寸减小分量和量化分量（基于动态范围缩小）处理成最终描述符，其可被进一步压缩。所得到的描述符与其他图像描述符（例如基于SIFT的描述符）相比，显着降低了错误率和显着更小的大小。

9. 发明授权

US09215869B1 Non-cadherin polypeptide potentitators of cry proteins 有权
标题翻译：非钙粘蛋白多肽抑制蛋白的增效剂
公开(公告)号：US09215869B1
公开(公告)日：2015-12-22
申请号：US13090830
申请日：2011-04-20
申请人： Michael J. Adang , Rui Zhang , Gang Hua
发明人： Michael J. Adang , Rui Zhang , Gang Hua
IPC分类号： A01N37/18
CPC分类号： A01N37/18 , A01N63/02 , A01N37/46
摘要： The subject invention relates in part to fragments of non-cadherin Cry toxin binding proteins, wherein the fragments potentiate, or act as synergists with, the insecticidal activity of Cry proteins. In some preferred embodiments, the binding protein (a Cry protein receptor on insect midgut cells) is an aminopeptidase. In preferred embodiments, the fragment comprises a Cry protein binding region.
摘要翻译：本发明部分涉及非钙粘蛋白Cry毒素结合蛋白的片段，其中片段加强Cry蛋白的杀虫活性，或作为增效剂。在一些优选的实施方案中，结合蛋白（昆虫中肠细胞上的Cry蛋白受体）是氨基肽酶。在优选的实施方案中，片段包含Cry蛋白结合区。

10. 发明授权

US08526684B2 Flexible image comparison and face matching application 有权
标题翻译：灵活的图像比较和面部匹配应用
公开(公告)号：US08526684B2
公开(公告)日：2013-09-03
申请号：US12637486
申请日：2009-12-14
申请人： Amir Akbarzadeh , Gang Hua
发明人： Amir Akbarzadeh , Gang Hua
IPC分类号： G06K9/00
CPC分类号： G06K9/6212 , G06K9/00288
摘要： Two faces may be compared by calculating distances between different regions of the windows, and choosing one of the distances as the difference between the images. Two images are examined to detect the location of the face in the images. The faces may then be geometrically and photometrically rectified. A sliding window that is smaller than the whole face may be positioned at various locations over the images, and a descriptor is calculated for each window position. The descriptor for a window at one location in one image is compared with descriptors for windows in the neighborhood of that location in the other image. The lowest distance between window descriptors is chosen. The process is repeated for all window positions, resulting in a set of distances. The distances are sorted, and one of the distances is chosen to represent the difference between the two faces.
摘要翻译：可以通过计算窗口的不同区域之间的距离并选择其中一个距离作为图像之间的差异来比较两个面。检查两个图像以检测图像中的脸部的位置。然后可以几何和光学校正面。小于整个脸部的滑动窗口可以位于图像上的各个位置，并且为每个窗口位置计算描述符。将一个图像中一个位置的窗口的描述符与其他图像中该位置附近的窗口的描述符进行比较。选择窗口描述符之间的最小距离。对所有窗口位置重复该过程，产生一组距离。距离被分类，并且选择一个距离来表示两个面之间的差异。

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