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51. 发明授权

US08774509B1 Method and system for creating a two-dimensional representation of an image based upon local representations throughout the image structure 有权
标题翻译：基于整个图像结构中的局部表示来创建图像的二维表示的方法和系统
公开(公告)号：US08774509B1
公开(公告)日：2014-07-08
申请号：US13410199
申请日：2012-03-01
申请人： Jay Yagnik , Douglas Eck
发明人： Jay Yagnik , Douglas Eck
IPC分类号： G06K9/00
CPC分类号： G06T9/00 , G06K9/4642 , G06K9/6218
摘要： A system computes a vectorial representation for each of a set of initial patches in an image and compares the vectorial representation for each initial patch with vectorial representations of nearby patches. Each nearby patch is within a distance from an initial patch. The system applies an ordinal coding algorithm on the comparison results between the vectorial representations for the initial patches and vectorial representations of nearby patches to generate a two-dimensional representation of the image indicating a repeating pattern within the image.
摘要翻译：系统计算图像中的一组初始补丁中的每一个的向量表示，并将每个初始补丁的向量表示与附近补丁的向量表示进行比较。每个附近的补丁距离初始补丁有一段距离。该系统对初始补丁的矢量表示和附近补丁的向量表示之间的比较结果应用序数编码算法，以生成指示图像内的重复图案的图像的二维表示。

52. 发明授权

US08676803B1 Clustering images 有权
标题翻译：聚集图像
公开(公告)号：US08676803B1
公开(公告)日：2014-03-18
申请号：US12612650
申请日：2009-11-04
申请人： Thomas Leung , Jay Yagnik
发明人： Thomas Leung , Jay Yagnik
IPC分类号： G06F17/30
CPC分类号： G06F17/30268 , G06F17/30265
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for clustering images. In one aspect a system includes one or more computers configured to, for each of a plurality of digital images, associate extrinsic image-related information with each individual image, the extrinsic image-related information including text information and co-click data for the individual image, assign images from the plurality of images to one or more of the clusters of images based on the extrinsic information associated with each of the plurality of images, receive in the search system a user query from a user device, identify by operation of the search system one or more clusters of images that match the query, and provide one or more cluster results, where each cluster result provides information about an identified cluster.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的用于聚类图像的计算机程序。在一个方面，一种系统包括：一个或多个计算机，被配置为针对多个数字图像中的每一个，将每个独立图像相关联的外在图像相关信息，所述外在图像相关信息包括个体的文本信息和共同点击数据图像，基于与所述多个图像中的每一个相关联的所述外在信息，将来自所述多个图像的图像分配给所述图像群集中的一个或多个，在所述搜索系统中从用户装置接收用户查询，搜索系统与查询匹配的一个或多个图像集群，并提供一个或多个集群结果，其中每个集群结果提供关于所识别的集群的信息。

53. 发明授权

US08537175B1 Video enhancement for large scale applications 有权
标题翻译：适用于大规模应用的视频增强
公开(公告)号：US08537175B1
公开(公告)日：2013-09-17
申请号：US12625822
申请日：2009-11-25
申请人： George Toderici , Jay Yagnik
发明人： George Toderici , Jay Yagnik
IPC分类号： G09G5/02 , G06T15/50 , G06T15/60
CPC分类号： G06T5/008 , G06T2207/10016 , G06T2207/20012
摘要： A video enhancement server enhances a video. A scene segmentation module detects scene boundaries and segments the video into a number of scenes. For each frame in a given scene, a local white level and a local black level are determined from the distribution of pixel luminance values in the frame. A global white level and global black level are also determined from the distribution of pixel luminance values throughout the scene. Weighted white levels and black levels are determined for each frame as a weighted combination of the local and global levels. The video segmentation server then applies histogram stretching and saturation adjustment to each frame using the weighted white levels and black levels to determine enhanced pixel luminance values. An enhanced video comprising the enhanced pixel luminance values is stored to a video server for serving to clients.
摘要翻译：视频增强服务器增强视频。场景分割模块检测场景边界并将视频分割成多个场景。对于给定场景中的每个帧，从帧中的像素亮度值的分布确定局部白电平和局部黑电平。全局白电平和全局黑电平也由整个场景中像素亮度值的分布确定。为每个帧确定加权白电平和黑电平作为本地和全局电平的加权组合。然后，视频分割服务器使用加权的白电平和黑电平对每个帧应用直方图拉伸和饱和度调整，以确定增强的像素亮度值。包括增强像素亮度值的增强视频被存储到视频服务器以供客户端服务。

54. 发明授权

US08429212B1 Training scoring models optimized for highly-ranked results 失效
公开(公告)号：US08429212B1
公开(公告)日：2013-04-23
申请号：US13342532
申请日：2012-01-03
申请人： Samy Bengio , Gal Chechik , Sergey Ioffe , Jay Yagnik
发明人： Samy Bengio , Gal Chechik , Sergey Ioffe , Jay Yagnik
IPC分类号： G06F17/00
CPC分类号： G06K9/66 , G06F17/30244 , G06F17/3053 , G06K9/6267 , Y10S707/913 , Y10S707/915
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training scoring models. One method includes storing data identifying a plurality of positive and a plurality of negative training images for a query. The method further includes selecting a first image from either the positive group of images or the negative group of images, and applying a scoring model to the first image. The method further includes selecting a plurality of candidate images from the other group of images, applying the scoring model to each of the candidate images, and then selecting a second image from the candidate images according to scores for the images. The method further includes determining that the scores for the first image and the second image fail to satisfy a criterion, updating the scoring model, and storing the updated scoring model.

55. 发明授权

US08396325B1 Image enhancement through discrete patch optimization 有权
标题翻译：通过离散补丁优化的图像增强
公开(公告)号：US08396325B1
公开(公告)日：2013-03-12
申请号：US12430812
申请日：2009-04-27
申请人： Vivek Kwatra , Mei Han , Jay Yagnik
发明人： Vivek Kwatra , Mei Han , Jay Yagnik
IPC分类号： G06K9/36
CPC分类号： G06T7/33
摘要： An image processing system enhances the resolution of an original image using higher-resolution image data from other images. The image processing system defines a plurality of overlapping partitions for the original image, each partition defining a set of non-overlapping site patches. During an optimization phase, the system identifies, for site patches of the original images, label patches within related images that are of most relevance. During a rendering phase independent of the optimization phase, an output image with enhanced resolution is synthesized by substituting, for site patches of the original image, the identified relevant label patches from the related images.
摘要翻译：图像处理系统使用来自其他图像的更高分辨率图像数据增强原始图像的分辨率。图像处理系统为原始图像定义多个重叠的分区，每个分区定义一组不重叠的站点块。在优化阶段期间，系统会针对最相关的相关图像中的原始图像的贴片进行标签贴图。在独立于优化阶段的渲染阶段期间，通过从相关图像中替换原始图像的位置贴片来识别识别的相关标签贴图来合成具有增强分辨率的输出图像。

56. 发明授权

US08340449B1 Three-dimensional wavelet based video fingerprinting 有权
公开(公告)号：US08340449B1
公开(公告)日：2012-12-25
申请号：US13250494
申请日：2011-09-30
申请人： Jay Yagnik , Henry A. Rowley , Sergey Ioffe
发明人： Jay Yagnik , Henry A. Rowley , Sergey Ioffe
IPC分类号： G06K9/00 , G06K9/46
CPC分类号： G06K9/00711 , H04N21/23418
摘要： A method and system generates and compares fingerprints for videos in a video library. The video fingerprints provide a compact representation of the spatial and sequential characteristics of the video that can be used to quickly and efficiently identify video content. Because the fingerprints are based on spatial and sequential characteristics rather than exact bit sequences, visual content of videos can be effectively compared even when there are small differences between the videos in compression factors, source resolutions, start and stop times, frame rates, and so on. Comparison of video fingerprints can be used, for example, to search for and remove copyright protected videos from a video library. Further, duplicate videos can be detected and discarded in order to preserve storage space.

57. 发明授权

US08301498B1 Video content analysis for automatic demographics recognition of users and videos 有权
标题翻译：用于用户和视频的自动人口统计识别的视频内容分析
公开(公告)号：US08301498B1
公开(公告)日：2012-10-30
申请号：US13488126
申请日：2012-06-04
申请人： Corinna Cortes , Sanjiv Kumar , Ameesh Makadia , Gideon Mann , Jay Yagnik , Ming Zhao
发明人： Corinna Cortes , Sanjiv Kumar , Ameesh Makadia , Gideon Mann , Jay Yagnik , Ming Zhao
IPC分类号： G06Q30/00 , G06N5/02
CPC分类号： H04N21/2407 , G06F17/30784 , G06F17/30817 , G06F17/3082 , G06F17/30828 , G06K9/00711 , H04N21/23418 , H04N21/25883 , H04N21/4668 , H04N21/4826
摘要： A video demographics analysis system selects a training set of videos to use to correlate viewer demographics and video content data. The video demographics analysis system extracts demographic data from viewer profiles related to videos in the training set and creates a set of demographic distributions, and also extracts video data from videos in the training set. The video demographics analysis system correlates the viewer demographics with the video data of videos viewed by that viewer. Using the prediction model produced by the machine learning process, a new video about which there is no a priori knowledge can be associated with a predicted demographic distribution specifying probabilities of the video appealing to different types of people within a given demographic category, such as people of different ages within an age demographic category.
摘要翻译：视频人口统计分析系统选择用于将观众人口特征和视频内容数据相关联的一组视频。视频人口统计分析系统从与训练集中的视频相关的观众简档中提取人口统计学数据，并创建一组人口分布，并从训练集中的视频中提取视频数据。视频人口统计分析系统将观众人口统计学与观众观看的视频的视频数据相关联。使用机器学习过程产生的预测模型，可以将预测的人口分布与预测的人口分布相关联，所述预测人口统计分布规定了给定人口统计学类别中的不同类型的人的视频的概率，例如人在不同年龄的人口统计学类别。

58. 发明授权

US08165414B1 Vector transformation for indexing, similarity search and classification 有权
标题翻译：矢量变换索引，相似搜索和分类
公开(公告)号：US08165414B1
公开(公告)日：2012-04-24
申请号：US13288706
申请日：2011-11-03
申请人： Jay Yagnik
发明人： Jay Yagnik
IPC分类号： G06K9/40 , G06E1/00
CPC分类号： G06F17/3002 , G06K2009/4695
摘要： A feature vector is encoded into a sparse binary vector. The feature vector is retrieved, for example from storage or a feature vector generator. The feature vector represents a media object or other data object. One or more permutations are generated, the dimensionality of the generated permutations equivalent to the dimensionality of the feature vector. The permutations may be generated randomly or formulaically. The feature vector is permuted with the one or more permutations, creating one or more permuted feature vectors. The permuted feature vectors are truncated according to a selected window size. The indexes representing the maximum values of the permuted feature vectors are identified and encoded using one-hot encoding, producing one or more sparse binary vectors. The sparse binary vectors may be concatenated into a single sparse binary vector and stored. The sparse binary vector may be used in the similarity search, indexing or categorization of media objects.
摘要翻译：特征向量被编码成稀疏二进制向量。例如从存储或特征向量生成器检索特征向量。特征向量表示媒体对象或其他数据对象。产生一个或多个排列，所产生的排列的维数等于特征向量的维数。排列可以随机或公式地产生。特征向量与一个或多个排列置换，创建一个或多个置换的特征向量。根据所选择的窗口尺寸来截断重排的特征向量。代表置换特征向量的最大值的索引使用单热编码进行识别和编码，产生一个或多个稀疏二进制向量。稀疏二进制向量可以被级联成单个稀疏二进制向量并被存储。稀疏二进制向量可以用于媒体对象的相似搜索，索引或分类。

59. 发明授权

US08131786B1 Training scoring models optimized for highly-ranked results 有权
标题翻译：培训评分模型针对高排名结果进行了优化
公开(公告)号：US08131786B1
公开(公告)日：2012-03-06
申请号：US12624001
申请日：2009-11-23
申请人： Samy Bengio , Gal Chechik , Sergey Ioffe , Jay Yagnik
发明人： Samy Bengio , Gal Chechik , Sergey Ioffe , Jay Yagnik
IPC分类号： G06F17/00
CPC分类号： G06K9/66 , G06F17/30244 , G06F17/3053 , G06K9/6267 , Y10S707/913 , Y10S707/915
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training scoring models. One method includes storing data identifying a plurality of positive and a plurality of negative training images for a query. The method further includes selecting a first image from either the positive group of images or the negative group of images, and applying a scoring model to the first image. The method further includes selecting a plurality of candidate images from the other group of images, applying the scoring model to each of the candidate images, and then selecting a second image from the candidate images according to scores for the images. The method further includes determining that the scores for the first image and the second image fail to satisfy a criterion, updating the scoring model, and storing the updated scoring model.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于训练评分模型。一种方法包括存储识别用于查询的多个正训练图像和多个负训练图像的数据。该方法还包括从图像的正组或负图像组中选择第一图像，以及将评分模型应用于第一图像。该方法还包括从另一组图像中选择多个候选图像，将评分模型应用于每个候选图像，然后根据图像的分数从候选图像中选择第二图像。该方法还包括确定第一图像和第二图像的分数不能满足标准，更新评分模型，并存储更新的评分模型。

60. 发明授权

US07827123B1 Graph based sampling 有权
标题翻译：基于图形的抽样
公开(公告)号：US07827123B1
公开(公告)日：2010-11-02
申请号：US11840139
申请日：2007-08-16
申请人： Jay Yagnik
发明人： Jay Yagnik
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： An iterative method of sampling real world event data to generate a subset of data that is used for training a classifier. Graph Based Sampling uses an iterative process of evaluating and adding randomly selected event data sets to a training data set. In Graph Based Sampling, at each iteration, a two event data sets are randomly selected from a stored plurality of event data sets. A proximity function is used to generate a correlation or similarity value between each of these randomly selected real world event data sets, and the current training data set. One of the randomly selected event data sets is then added to the training data set based on the proximity value. This process of selection and addition is repeated until the subset of training set is a pre-determined size.
摘要翻译：对现实世界事件数据进行采样以生成用于训练分类器的数据子集的迭代方法。基于图形的采样使用迭代过程来评估和添加随机选择的事件数据集到训练数据集。在基于图形的抽样中，在每次迭代中，从存储的多个事件数据集中随机选择两个事件数据集。接近函数用于在这些随机选择的真实世界事件数据集和当前训练数据集之间产生相关性或相似性值。然后将随机选择的事件数据集之一基于接近度值加到训练数据集中。重复该选择和添加过程，直到训练集的子集为预定大小。

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