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公开(公告)号：US08942467B2
公开(公告)日：2015-01-27
申请号：US13428554
申请日：2012-03-23
申请人： Fatih Porikli , Yi Wang
发明人： Fatih Porikli , Yi Wang
IPC分类号： G06K9/62
摘要： Blocking artifacts are reduced by projecting each patch obtained from an input image onto a set of bases vectors to determine multiple representations for each patch. The set of bases vectors are learned from a training image, and the bases vectors include a full basis vector, and one or two subspace bases vectors. An optimal basis vector is determined in the set of bases vectors for each patch according to the projection. A threshold is applied to coefficients of the optimal basis vector to determine a filtered representation for each patch, and a reconstructed patch is generated using the filtered representation. Then, the aggregating the reconstructed patches are aggregated to produce an output image.
摘要翻译： 通过将从输入图像获得的每个贴片投影到一组基本矢量上以确定每个贴片的多个表示来减少阻挡伪影。 从训练图像中学习基本矢量集合，并且基本矢量包括全基矢量和一个或两个子空间基矢量。 根据投影，在每个贴片的基准矢量集合中确定最优基矢量。 将阈值应用于最佳基本矢量的系数，以确定每个贴片的滤波表示，并且使用滤波后的表示生成重建的贴片。 然后，聚合重建的片段被聚合以产生输出图像。
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公开(公告)号：US20130251245A1
公开(公告)日：2013-09-26
申请号：US13428554
申请日：2012-03-23
申请人： Fatih Porikli , Yi Wang
发明人： Fatih Porikli , Yi Wang
摘要： Blocking artifacts are reduced by projecting each patch obtained from an input image onto a set of bases vectors to determine multiple representations for each patch. The set of bases vectors are learned from a training image, and the bases vectors include a full basis vector, and one or two subspace bases vectors. An optimal basis vector is determined in the set of bases vectors for each patch according to the projection. A threshold is applied to coefficients of the optimal basis vector to determine a filtered representation for each patch, and a reconstructed patch is generated using the filtered representation. Then, the aggregating the reconstructed patches are aggregated to produce an output image.
摘要翻译： 通过将从输入图像获得的每个贴片投影到一组基本矢量上以确定每个贴片的多个表示来减少阻挡伪影。 从训练图像中学习基本矢量集合，并且基本矢量包括全基矢量和一个或两个子空间基矢量。 根据投影，在每个贴片的基准矢量集合中确定最优基矢量。 将阈值应用于最佳基本矢量的系数，以确定每个贴片的滤波表示，并且使用滤波后的表示生成重建的贴片。 然后，聚合重建的片段被聚合以产生输出图像。
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公开(公告)号：US20130223734A1
公开(公告)日：2013-08-29
申请号：US13405155
申请日：2012-02-24
申请人： Oncel Tuzel , Fatih Porikli , Chinmay Hegde
发明人： Oncel Tuzel , Fatih Porikli , Chinmay Hegde
CPC分类号： G06T3/4053
摘要： A natural input image is upscaled, first by interpolation. Second, edges in the interpolated image are sharpened by a lion-parametric patch transform. The result is decomposed into an edge layer and a detail layer. Only pixels in the detail layer enhanced, and the enhanced detail layer is merged with the edge layer to produce a high resolution version of the input image.
摘要翻译： 自然输入图像放大，首先通过插值。 第二，插值图像中的边缘通过狮子参数补丁变换来锐化。 结果被分解成边缘层和细节层。 只有细节层中的像素增强，并且增强的细节层与边缘层合并以产生输入图像的高分辨率版本。
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14.发明申请公开(公告)号：US20120254077A1
公开(公告)日：2012-10-04
申请号：US13076749
申请日：2011-03-31
申请人： Fatih Porikli , Huseyin Ozkan
发明人： Fatih Porikli , Huseyin Ozkan
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： Frequency features to be used for binary classification of data using a linear classifier are selected by determining a set of hypotheses in a d-dimensional space using d-dimensional labeled training data. A mapping function is constructed for each hypothesis. The mapping functions are applied to the training data to generate frequency features, and a subset of the frequency are selecting iteratively. The linear function is then trained using the subset of frequency features and labels of the training data.
摘要翻译： 使用线性分类器对数据的二进制分类使用的频率特征是通过使用d维标记的训练数据确定d维空间中的一组假设来选择的。 为每个假设构建映射函数。 将映射函数应用于训练数据以产生频率特征，并且频率的子集被迭代地选择。 然后使用训练数据的频率特征和标签的子集来训练线性函数。
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公开(公告)号：US20070183629A1
公开(公告)日：2007-08-09
申请号：US11352145
申请日：2006-02-09
申请人： Fatih Porikli , Oncel Tuzel
发明人： Fatih Porikli , Oncel Tuzel
CPC分类号： G06K9/32 , G06T7/251 , G06T2207/10016 , G06T2207/30196
摘要： A method is provided for tracking a non-rigid object in a sequence of frames of a video. Features of an object are extracted from the video. The features include locations of pixels and properties of the pixels. The features are used to construct a covariance matrix. The covariance matrix is used as a descriptor of the object for tracking purposes. Object deformations and appearance changes are managed with an update mechanism that is based on Lie algebra averaging.
摘要翻译： 提供一种用于跟踪视频帧中的非刚性对象的方法。 从视频中提取对象的特征。 这些特征包括像素的位置和像素的属性。 这些特征用于构造协方差矩阵。 协方差矩阵用作跟踪目的的对象的描述符。 对象变形和外观变化通过基于李代数平均的更新机制进行管理。
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公开(公告)号：US20050190975A1
公开(公告)日：2005-09-01
申请号：US10787667
申请日：2004-02-26
申请人： Fatih Porikli , Xiaokun Li
发明人： Fatih Porikli , Xiaokun Li
CPC分类号： G06K9/00711 , G06K9/00335
摘要： A method detects traffic events in a compressed video. Feature vectors are extracted from the compressed video. The feature vector are provided to a Gaussian mixture hidden Markov model. Then, a maximum likelihood of the Gaussian mixture hidden Markov model is determined to classify the plurality of feature vector as traffic events.
摘要翻译： 一种方法检测压缩视频中的交通事件。 从压缩视频中提取特征向量。 将特征向量提供给高斯混合隐马尔科夫模型。 然后，确定高斯混合隐马尔可夫模型的最大似然度，将多个特征向量分类为交通事件。
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17.发明授权Method for clustering samples with weakly supervised kernel mean shift matrices 有权用弱监督核平均移位矩阵聚类样本的方法公开(公告)号：US08296248B2
公开(公告)日：2012-10-23
申请号：US12495614
申请日：2009-06-30
申请人： Cuneyt Oncel Tuzel , Fatih Porikli
发明人： Cuneyt Oncel Tuzel , Fatih Porikli
IPC分类号： G06F15/18
CPC分类号： G06K9/6226 , G06N99/005
摘要： A method clusters samples using a mean shift procedure. A kernel matrix is determined from the samples in a first dimension. A constraint matrix and a scaling matrix are determined from a constraint set. The kernel matrix is projected to a feature space having a second dimension using the constraint matrix, wherein the second dimension is higher than the first dimension. Then, the samples are clustered according to the kernel matrix.
摘要翻译： 方法使用平均偏移程序聚类样本。 从第一维度的样本确定核心矩阵。 从约束集确定约束矩阵和缩放矩阵。 使用约束矩阵将核心矩阵投影到具有第二维度的特征空间，其中第二维度高于第一维度。 然后，根据核心矩阵对样本进行聚类。
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公开(公告)号：US20120251013A1
公开(公告)日：2012-10-04
申请号：US13076522
申请日：2011-03-31
申请人： Fatih Porikli
发明人： Fatih Porikli
IPC分类号： G06K9/36
摘要： A method compresses an image partitioned into blocks of pixels, for each block the method converts the block to a 2D matrix. The matrix is decomposing into a column matrix and a row matrix, wherein a width of the column matrix is substantially smaller than a height of the column matrix and the height of the row matrix is substantially smaller than the width of the row matrix. The column matrix and the row matrix are compressed, and the compressed matrices are then combined to form a compressed image.
摘要翻译： 一种方法将分割成像素块的图像压缩，对于每个块，该方法将块转换为2D矩阵。 矩阵分解为列矩阵和行矩阵，其中列矩阵的宽度基本上小于列矩阵的高度，并且行矩阵的高度基本上小于行矩阵的宽度。 列矩阵和行矩阵被压缩，然后将压缩的矩阵组合以形成压缩图像。
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公开(公告)号：US20060290780A1
公开(公告)日：2006-12-28
申请号：US11167611
申请日：2005-06-27
申请人： Fatih Porikli
发明人： Fatih Porikli
IPC分类号： H04N7/18
CPC分类号： G06K9/6277 , G06K9/346 , G06K9/38 , G06T7/215
摘要： A method models a scene. A video is acquired of the scene, and for each frame of the video, the method updates a set of background models for each pixel; a set of shadow models for each pixel; a set of shadow flow vectors for each color; and a background shadow map. Each pixel in each background model and each shadow model is represented by multiple layers. Each layer includes Gaussian distributions and each Gaussian distribution includes a mean and a covariance. The covariance is an inverse Wishart distribution and the updating is according to a recursive Bayesian estimation process.
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公开(公告)号：US20060222205A1
公开(公告)日：2006-10-05
申请号：US11097400
申请日：2005-04-01
申请人： Fatih Porikli , Oncel Tuzel
发明人： Fatih Porikli , Oncel Tuzel
CPC分类号： G06T7/20 , G06K9/32 , G06K9/4652 , G06K9/6212 , G06K2009/3291
摘要： A method tracks a moving object in a video acquired of a scene with a camera. A background model is maintained for each frame, and moving objects are detected according to changes in the background model. An object model is maintained for the moving object, and kernels are generated for the moving object. A mean-shift process is applied to each kernel in each frame to determine a likelihood of an estimated location of the moving object in each frame, according to the background models, the object model, and the mean shift kernels to track the moving object in the video.
摘要翻译： 一种方法利用相机跟踪场景获取的视频中的移动物体。 为每个帧维护一个背景模型，并根据背景模型的变化来检测移动的对象。 为运动对象维护对象模型，并为运动对象生成内核。 平均移位过程被应用于每个帧中的每个内核，以根据背景模型，对象模型和用于跟踪移动对象的平均移位内核来确定每个帧中的运动对象的估计位置的可能性 视频。
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