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公开(公告)号：US08218880B2
公开(公告)日：2012-07-10
申请号：US12129515
申请日：2008-05-29
申请人： Deli Zhao , Zhouchen Lin , Rong Xiao , Xiaoou Tang
发明人： Deli Zhao , Zhouchen Lin , Rong Xiao , Xiaoou Tang
CPC分类号： G06K9/00275 , G06K9/6234
摘要： An exemplary method for extracting discriminant feature of samples includes providing data for samples in a multidimensional space; based on the data, computing local similarities for the samples; mapping the local similarities to weights; based on the mapping, formulating an inter-class scatter matrix and an intra-class scatter matrix; and based on the matrices, maximizing the ratio of inter-class scatter to intra-class scatter for the samples to provide discriminate features of the samples. Such a method may be used for classifying samples, recognizing patterns, or other tasks. Various other methods, devices, system, etc., are also disclosed.
摘要翻译： 用于提取样本的判别特征的示例性方法包括在多维空间中提供样本的数据; 基于数据，计算样本的局部相似度; 将局部相似性映射到权重; 基于映射，制定类间散布矩阵和类内散布矩阵; 并且基于矩阵，最大化样本之间的类间散射与类内散射的比率以提供样本的区别特征。 这种方法可用于分类样本，识别模式或其他任务。 还公开了各种其它方法，装置，系统等。
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公开(公告)号：US07996343B2
公开(公告)日：2011-08-09
申请号：US12242421
申请日：2008-09-30
申请人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
发明人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
IPC分类号： G06F11/00
CPC分类号： G06K9/6234 , G06K9/6252
摘要： Described is using semi-Riemannian geometry in supervised learning to learn a discriminant subspace for classification, e.g., labeled samples are used to learn the geometry of a semi-Riemannian submanifold. For a given sample, the K nearest classes of that sample are determined, along with the nearest samples that are in other classes, and the nearest samples in that sample's same class. The distances between these samples are computed, and used in computing a metric matrix. The metric matrix is used to compute a projection matrix that corresponds to the discriminant subspace. In online classification, as a new sample is received, it is projected into a feature space by use of the projection matrix and classified accordingly.
摘要翻译： 描述了在监督学习中使用半黎曼几何学习学习用于分类的判别子空间，例如，标记的样本用于学习半黎曼子流形歧管的几何形状。 对于给定的样本，该样本的K个最近类别以及其他类别中最近的样本以及该样本同一类中最近的样本进行确定。 计算这些样本之间的距离，并用于计算度量矩阵。 度量矩阵用于计算与判别子空间对应的投影矩阵。 在线分类中，作为收到的新样本，通过使用投影矩阵将其投影到特征空间中并进行分类。
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公开(公告)号：US20090097772A1
公开(公告)日：2009-04-16
申请号：US11871764
申请日：2007-10-12
申请人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
发明人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
IPC分类号： G06K9/40
CPC分类号： G06K9/6248
摘要： Systems and methods perform Laplacian Principal Components Analysis (LPCA). In one implementation, an exemplary system receives multidimensional data and reduces dimensionality of the data by locally optimizing a scatter of each local sample of the data. The optimization includes summing weighted distances between low dimensional representations of the data and a mean. The weights of the distances can be determined by a coding length of each local data sample. The system can globally align the locally optimized weighted scatters of the local samples and provide a global projection matrix. The LPCA improves performance of such applications as face recognition and manifold learning.
摘要翻译： 系统和方法执行拉普拉斯主成分分析（LPCA）。 在一个实现中，示例性系统通过局部优化数据的每个局部采样的散射来接收多维数据并且降低数据的维度。 优化包括对数据的低维表示和平均值之间的加权距离求和。 距离的权重可以通过每个本地数据样本的编码长度来确定。 该系统可以对局部采样的局部优化加权散射进行全局对齐，并提供全局投影矩阵。 LPCA可以改善诸如面部识别和歧管学习等应用的性能。
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公开(公告)号：US08064697B2
公开(公告)日：2011-11-22
申请号：US11871764
申请日：2007-10-12
申请人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
发明人： Deli Zhao , Zhouchen Lin , Xiaoou Tang
CPC分类号： G06K9/6248
摘要： Systems and methods perform Laplacian Principal Components Analysis (LPCA). In one implementation, an exemplary system receives multidimensional data and reduces dimensionality of the data by locally optimizing a scatter of each local sample of the data. The optimization includes summing weighted distances between low dimensional representations of the data and a mean. The weights of the distances can be determined by a coding length of each local data sample. The system can globally align the locally optimized weighted scatters of the local samples and provide a global projection matrix. The LPCA improves performance of such applications as face recognition and manifold learning.
摘要翻译： 系统和方法执行拉普拉斯主成分分析（LPCA）。 在一个实现中，示例性系统通过局部优化数据的每个局部采样的散射来接收多维数据并且降低数据的维度。 优化包括对数据的低维表示和平均值之间的加权距离求和。 距离的权重可以通过每个本地数据样本的编码长度来确定。 该系统可以对局部采样的局部优化加权散射进行全局对齐，并提供全局投影矩阵。 LPCA可以改善诸如面部识别和歧管学习等应用的性能。
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公开(公告)号：US07692647B2
公开(公告)日：2010-04-06
申请号：US11532052
申请日：2006-09-14
申请人： Zhouchen Lin , Lifeng Wang , Tian Fang , Xu Yang , Xuan Yu , Jian Wang , Xiaoou Tang
发明人： Zhouchen Lin , Lifeng Wang , Tian Fang , Xu Yang , Xuan Yu , Jian Wang , Xiaoou Tang
CPC分类号： G06T13/60 , G06T2210/56
摘要： Real-time rendering of realistic rain is described. In one aspect, image samples of real rain and associated information are automatically modeled in real-time to generate synthetic rain particles in view of respective scene radiances of target video content frames. The synthetic rain particles are rendered in real-time using pre-computed radiance transfer with uniform random distribution across respective frames of the target video content.
摘要翻译： 描述了实时降雨的实时渲染。 在一个方面，根据目标视频内容帧的相应场景辐射，实时地自动建模真实雨和相关信息的图像样本以产生合成雨粒子。 使用预先计算的辐射传输，通过目标视频内容的各个帧上的均匀随机分布实时地渲染合成雨粒子。
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公开(公告)号：US20100076723A1
公开(公告)日：2010-03-25
申请号：US12235927
申请日：2008-09-23
申请人： Wei Zhang , Zhouchen Lin , Xiaoou Tang
发明人： Wei Zhang , Zhouchen Lin , Xiaoou Tang
CPC分类号： G06F17/30598 , G06K9/6234
摘要： Tensor linear Laplacian discrimination for feature extraction is disclosed. One embodiment comprises generating a contextual distance based sample weight and class weight, calculating a within-class scatter using the at least one sample weight and a between-class scatter for multiple classes of data samples in a sample set using the class weight, performing a mode-k matrix unfolding on scatters and generating at least one orthogonal projection matrix.
摘要翻译： 公开了用于特征提取的张量线性拉普拉斯判别。 一个实施例包括生成基于上下文距离的样本权重和类权重，使用所述至少一个样本权重来计算类内散度，以及使用类权重在样本集合中的多类数据样本之间进行类间散射，执行 mode-k矩阵在散射上展开并生成至少一个正交投影矩阵。
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公开(公告)号：US07609271B2
公开(公告)日：2009-10-27
申请号：US11428195
申请日：2006-06-30
申请人： Zhouchen Lin , Lifeng Wang , Yunbo Wang , Jian Wang , Xiaoou Tang
发明人： Zhouchen Lin , Lifeng Wang , Yunbo Wang , Jian Wang , Xiaoou Tang
IPC分类号： G06T13/00
CPC分类号： G06T13/80 , G09G5/00 , G09G2340/0414 , G09G2340/0421
摘要： A strategy is described for producing an animated scene from multiple high resolution still images. The strategy involves: creating a graph based on an analysis of similarity among the plural still images; performing partial temporal order recovery to define a partial ordering among the plural still images; and extracting an output sequence from the plural still images using second-order Markov Chain analysis, using the partial ordering as a reference. The strategy can perform the above-described analysis with respect to multiple independent animated regions (IARs) within the still images. Further, the strategy can decompose any IAR with a significant amount of motion into multiple semi-independent animated regions (SIARs). The SIARs are defined to be weakly interdependent.
摘要翻译： 描述了从多个高分辨率静止图像生成动画场景的策略。 该策略涉及：基于对多个静止图像之间的相似性的分析来创建图; 执行部分时间顺序恢复以限定所述多个静止图像中的部分排序; 以及使用部分排序作为参考，使用二阶马尔可夫链分析从多个静止图像中提取输出序列。 该策略可以针对静止图像内的多个独立动画区域（IAR）执行上述分析。 此外，该策略可以将具有大量运动的任何IAR分解成多个半独立动画区域（SIAR）。 SIAR被定义为弱相互依赖。
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公开(公告)号：US20090080774A1
公开(公告)日：2009-03-26
申请号：US11860428
申请日：2007-09-24
申请人： Zhouchen Lin , Guangcan Liu , Xiaoou Tang
发明人： Zhouchen Lin , Guangcan Liu , Xiaoou Tang
IPC分类号： G06K9/34
摘要： This disclosure describes an integrated framework for class-unsupervised object segmentation. The class-unsupervised object segmentation occurs by integrating top-down constraints and bottom-up constraints on object shapes using an algorithm in an integrated manner. The algorithm describes a relationship among object parts and superpixels. This process forms object shapes with object parts and oversegments pixel images into the superpixels, with the algorithm in conjunction with the constraints. This disclosure describes computing a mask map from a hybrid graph, segmenting the image into a foreground object and a background, and displaying the foreground object from the background.
摘要翻译： 本公开描述了用于无人监督的对象分割的集成框架。 通过以集成的方式使用算法将自上而下的约束和自下而上的对象形状约束集成在一起，进行类无监督对象分割。 该算法描述了对象部分和超像素之间的关系。 该过程通过对象部分形成对象形状，并将像素图像监视到超像素中，该算法与约束相结合。 本公开描述了从混合图计算掩模图，将图像分割成前景对象和背景，以及从背景显示前景对象。
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公开(公告)号：US20080001950A1
公开(公告)日：2008-01-03
申请号：US11428195
申请日：2006-06-30
申请人： Zhouchen Lin , Lifeng Wang , Yunbo Wang , Jian Wang , Xiaoou Tang
发明人： Zhouchen Lin , Lifeng Wang , Yunbo Wang , Jian Wang , Xiaoou Tang
IPC分类号： G06T13/00
CPC分类号： G06T13/80 , G09G5/00 , G09G2340/0414 , G09G2340/0421
摘要： A strategy is described for producing an animated scene from multiple high resolution still images. The strategy involves: creating a graph based on an analysis of similarity among the plural still images; performing partial temporal order recovery to define a partial ordering among the plural still images; and extracting an output sequence from the plural still images using second-order Markov Chain analysis, using the partial ordering as a reference. The strategy can perform the above-described analysis with respect to multiple independent animated regions (IARs) within the still images. Further, the strategy can decompose any IAR with a significant amount of motion into multiple semi-independent animated regions (SIARs). The SIARs are defined to be weakly interdependent.
摘要翻译： 描述了从多个高分辨率静止图像生成动画场景的策略。 该策略涉及：基于对多个静止图像之间的相似性的分析来创建图; 执行部分时间顺序恢复以限定所述多个静止图像中的部分排序; 以及使用部分排序作为参考，使用二阶马尔可夫链分析从多个静止图像中提取输出序列。 该策略可以针对静止图像内的多个独立动画区域（IAR）执行上述分析。 此外，该策略可以将具有大量运动的任何IAR分解成多个半独立动画区域（SIAR）。 SIAR被定义为弱相互依赖。
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公开(公告)号：US20070195106A1
公开(公告)日：2007-08-23
申请号：US11276204
申请日：2006-02-17
申请人： Zhouchen Lin , Junfeng He , Xiaoou Tang
发明人： Zhouchen Lin , Junfeng He , Xiaoou Tang
IPC分类号： G09G5/02
CPC分类号： G06T1/0042 , G06T2201/0052 , H04N19/60 , H04N19/86
摘要： Systems and methods for detecting doctored JPEG images are described. In one aspect, a JPEG image is evaluated to determine if the JPEG image comprises double quantization effects of double quantized Discrete Cosine Transform coefficients. In response to results of these evaluation operations, the systems and methods determine whether the JPEG image has been doctored and identify any doctored portion.
摘要翻译： 描述用于检测编码的JPEG图像的系统和方法。 在一个方面，评估JPEG图像以确定JPEG图像是否包括双量化离散余弦变换系数的双量化效应。 响应于这些评估操作的结果，系统和方法确定JPEG图像是否被编辑并识别任何编辑部分。
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