公开(公告)号：US20100191689A1

公开(公告)日：2010-07-29

申请号：US12392987

申请日：2009-02-25

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： G06N5/02 ,  H04N7/10

CPC分类号： H04N21/2407 ,  G06F16/735 ,  G06F16/78 ,  G06F16/783 ,  G06F16/7867 ,  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。

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。

公开(公告)号：US20120272259A1

公开(公告)日：2012-10-25

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： H04N21/24

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。

公开(公告)号：US08213689B2

公开(公告)日：2012-07-03

申请号：US12172939

申请日：2008-07-14

申请人： Jay Yagnik ,  Ming Zhao

发明人： Jay Yagnik ,  Ming Zhao

IPC分类号： G06K9/00 ,  G06K9/62

CPC分类号： G06K9/00711 ,  G06F17/30781 ,  G06K9/00295 ,  G06K9/6255

摘要： Methods and systems for automated annotation of persons in video content are disclosed. In one embodiment, a method of identifying faces in a video includes the stages of: generating face tracks from input video streams; selecting key face images for each face track; clustering the face tracks to generate face clusters; creating face models from the face clusters; and correlating face models with a face model database. In another embodiment, a system for identifying faces in a video includes a face model database having face entries with face models and corresponding names, and a video face identifier module. In yet another embodiment, the system for identifying faces in a video can also have a face model generator.

摘要翻译： 公开了用于视频内容中的人的自动注释的方法和系统。 在一个实施例中，识别视频中的面部的方法包括以下阶段：从输入视频流生成面部曲面; 为每个脸部轨迹选择关键脸部图像; 聚集脸部轨迹以生成脸部群集; 从脸部群集中创建面部模型; 并将面部模型与面部模型数据库相关联。 在另一个实施例中，用于识别视频中的面部的系统包括具有面部表情和面部模型和对应名称的面部模型数据库，以及视频面部识别器模块。 在另一个实施例中，用于识别视频中的面部的系统还可以具有面部模型生成器。

公开(公告)号：US08792732B1

公开(公告)日：2014-07-29

申请号：US13559420

申请日：2012-07-26

申请人： Ming Zhao ,  Jay Yagnik

发明人： Ming Zhao ,  Jay Yagnik

IPC分类号： G06K9/46 ,  H04N5/14

CPC分类号： G06K9/6232 ,  G06K9/6215

摘要： An object recognition system performs a number of rounds of dimensionality reduction and consistency learning on visual content items such as videos and still images, resulting in a set of feature vectors that accurately predict the presence of a visual object represented by a given object name within an visual content item. The feature vectors are stored in association with the object name which they represent and with an indication of the number of rounds of dimensionality reduction and consistency learning that produced them. The feature vectors and the indication can be used for various purposes, such as quickly determining a visual content item containing a visual representation of a given object name.

摘要翻译： 对象识别系统对诸如视频和静止图像的视觉内容项目执行多次维数降低和一致性学习，导致一组特征向量，其精确地预测由一个对象名称表示的视觉对象的存在 视觉内容项目。 特征向量与它们所代表的对象名称相关联地存储，并且显示产生它们的维度降低和一致性学习的轮次数。 特征向量和指示可以用于各种目的，诸如快速确定包含给定对象名称的视觉表示的视觉内容项。

公开(公告)号：US08452778B1

公开(公告)日：2013-05-28

申请号：US12874015

申请日：2010-09-01

申请人： Yang Song ,  Ming Zhao ,  Jay Yagnik

发明人： Yang Song ,  Ming Zhao ,  Jay Yagnik

IPC分类号： G06F17/30 ,  G10L19/12

CPC分类号： G06F17/30799 ,  G06F17/30796 ,  G06K9/00711

摘要： A classifier training system trains adapted classifiers for classifying videos based at least in part on scores produced by application of text-based classifiers to textual metadata of the videos. Each classifier corresponds to a particular category, and when applied to a given video indicates whether the video represents the corresponding category. The classifier training system applies the text-based classifiers to textual metadata of the videos to obtain the scores, and also extracts features from content of the videos, combining the scores and the content features for a video into a set of hybrid features. The adapted classifiers are then trained on the hybrid features. The adaption of the text-based classifiers from the textual domain to the video domain allows the training of accurate video classifiers (the adapted classifiers) without requiring a large training set of authoritatively labeled videos.

摘要翻译： 分类器训练系统训练适用的分类器，用于至少部分地基于将基于文本的分类器应用于视频的文本元数据而产生的分数来分类视频。 每个分类器对应于特定类别，并且当应用于给定视频时指示视频是否表示相应类别。 分类器训练系统将基于文本的分类器应用于视频的文本元数据以获得分数，并且还从视频内容中提取特征，将视频的分数和内容特征组合成一组混合特征。 然后对适应的分类器对混合特征进行训练。 基于文本的分类器从文本域到视频域的适应允许训练准确的视频分类器（适应的分类器），而不需要大量的授权标签视频的训练集。

公开(公告)号：US08254699B1

公开(公告)日：2012-08-28

申请号：US12364390

申请日：2009-02-02

申请人： Ming Zhao ,  Jay Yagnik

发明人： Ming Zhao ,  Jay Yagnik

IPC分类号： G06K9/46 ,  G06K9/48 ,  H04N5/14 ,  G06E1/00

CPC分类号： G06K9/6232 ,  G06K9/6215

摘要： An object recognition system performs a number of rounds of dimensionality reduction and consistency learning on visual content items such as videos and still images, resulting in a set of feature vectors that accurately predict the presence of a visual object represented by a given object name within an visual content item. The feature vectors are stored in association with the object name which they represent and with an indication of the number of rounds of dimensionality reduction and consistency learning that produced them. The feature vectors and the indication can be used for various purposes, such as quickly determining a visual content item containing a visual representation of a given object name.

摘要翻译： 对象识别系统对诸如视频和静止图像的视觉内容项目执行多次维数降低和一致性学习，导致一组特征向量，其精确地预测由一个对象名称表示的视觉对象的存在 视觉内容项目。 特征向量与它们所代表的对象名称相关联地存储，并且显示产生它们的维度降低和一致性学习的轮次数。 特征向量和指示可以用于各种目的，诸如快速确定包含给定对象名称的视觉表示的视觉内容项。

公开(公告)号：US09684715B1

公开(公告)日：2017-06-20

申请号：US13415704

申请日：2012-03-08

申请人： David Ross ,  Jay Yagnik

发明人： David Ross ,  Jay Yagnik

IPC分类号： G06F17/30 ,  G06F17/00

CPC分类号： G06F17/30743 ,  G06F17/00 ,  G06F17/3074

摘要： This disclosure relates to audio identification using ordinal transformations. A media matching component receives a sample audio file. The sample audio file can include, for example, a cover song. The media matching component includes a vector component that computes a set of vectors using auditory feature values included in the sample audio file. A hashing component employs a hash function to generate a fingerprint, including a set of sub-fingerprints, for the sample audio file using the set of vectors. The fingerprint is invariant to variations including but not limited to variations in key, instrumentation, encoding formats, performers, performance conditions, arrangement, and/or recording and processing variations. An identification component determines if any reference audio files are similar to the sample audio file using the fingerprint and/or sub-fingerprints, and identifies any similar reference audio files.

公开(公告)号：US08805090B1

公开(公告)日：2014-08-12

申请号：US13368317

申请日：2012-02-07

申请人： Jay Yagnik ,  Sergey Ioffe

发明人： Jay Yagnik ,  Sergey Ioffe

IPC分类号： G06K9/68

CPC分类号： G06K9/6212

摘要： Systems and methods for measuring consistency between two objects based upon a rank of object elements instead of based upon the values of those object elements. Objects being compared can be represented by d-dimension feature vectors, U and V, where each dimension includes an associated value. U and V can be converted to rank vectors, P and Q, where values of U and V dimensions are replaced by an ordered rank or a function thereof. Analysis directed to the consistency between U and V can be accomplished by determining consistency between P and Q, which can be more efficient and more accurate, particularly with regard to illumination-invariant comparisons.

摘要翻译： 基于对象元素的等级而不是基于这些对象元素的值来测量两个对象之间的一致性的系统和方法。 被比较的对象可以由d维特征向量U和V表示，其中每个维度包括相关联的值。 U和V可以被转换为等级向量P和Q，其中U和V维度的值被有序等级或其功能所代替。 可以通过确定P和Q之间的一致性来实现对U和V之间的一致性的分析，这可以更有效和更准确，特别是在照明不变比较方面。

公开(公告)号：US08238669B2

公开(公告)日：2012-08-07

申请号：US12174366

申请日：2008-07-16

申请人： Michele Covell ,  Jay Yagnik ,  Jeff Faust ,  Shumeet Baluja

发明人： Michele Covell ,  Jay Yagnik ,  Jeff Faust ,  Shumeet Baluja

IPC分类号： G06K9/62 ,  H04N7/10 ,  H04N7/025

CPC分类号： G06K9/00758 ,  G06F17/30784

摘要： A system and method detects matches between portions of video content. A matching module receives an input video fingerprint representing an input video and a set of reference fingerprints representing reference videos in a reference database. The matching module compares the reference fingerprints and input fingerprints to generate a list of candidate segments from the reference video set. Each candidate segment comprises a time-localized portion of a reference video that potentially matches the input video. A classifier is applied to each of the candidate segments to classify the segment as a matching segment or a non-matching segment. A result is then outputted identifying a matching portion of a reference video from the reference video set based on the segments classified as matches.

摘要翻译： 系统和方法检测视频内容的部分之间的匹配。 匹配模块接收表示参考数据库中的参考视频的输入视频和一组参考指纹的输入视频指纹。 匹配模块比较参考指纹和输入指纹，以从参考视频集中生成候选片段的列表。 每个候选片段包括潜在地匹配输入视频的参考视频的时间局部化部分。 将分类器应用于每个候选片段以将片段分类为匹配片段或非匹配片段。 然后基于被分类为匹配的段，从参考视频集中输出标识参考视频的匹配部分的结果。