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1. 发明授权

US08611422B1 Endpoint based video fingerprinting 有权
公开(公告)号：US08611422B1
公开(公告)日：2013-12-17
申请号：US11765292
申请日：2007-06-19
申请人： Jay Yagnik , Henry A. Rowley , Sergey Ioffe
发明人： Jay Yagnik , Henry A. Rowley , Sergey Ioffe
IPC分类号： H04N7/12 , H04N11/02 , H04N11/04
CPC分类号： G06T1/0021 , G06F17/30784 , G06F17/30787 , G06K9/00744 , G06K9/00758
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 temporal locations of discontinuities in the video that can be used to quickly and efficiently identify video content. Discontinuities can be, for example, shot boundaries in the video frame sequence or silent points in the audio stream. Because the fingerprints are based on structural discontinuity 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. Furthermore, duplicate videos can be detected and discarded in order to preserve storage space.

2. 发明授权

US08094872B1 Three-dimensional wavelet based video fingerprinting 有权
标题翻译：基于三维小波的视频指纹识别
公开(公告)号：US08094872B1
公开(公告)日：2012-01-10
申请号：US11746339
申请日：2007-05-09
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 , H04L9/32 , H04N7/167
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.
摘要翻译：方法和系统生成并比较视频库中视频的指纹。视频指纹提供了可用于快速有效地识别视频内容的视频的空间和顺序特征的紧凑表示。因为指纹是基于空间和顺序特征而不是精确的比特序列，所以即使在压缩因素，源分辨率，开始和停止时间，帧率等之间的视频之间存在小的差异，也可以有效地比较视频的视觉内容上。可以使用比较视频指纹，例如，从视频库搜索和删除受版权保护的视频。此外，为了保存存储空间，可以检测和丢弃重复的视频。

3. 发明授权

US08611689B1 Three-dimensional wavelet based video fingerprinting 有权
标题翻译：基于三维小波的视频指纹识别
公开(公告)号：US08611689B1
公开(公告)日：2013-12-17
申请号：US12968825
申请日：2010-12-15
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 , H04N7/167 , H04L9/32
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.
摘要翻译：方法和系统生成并比较视频库中视频的指纹。视频指纹提供了可用于快速有效地识别视频内容的视频的空间和顺序特征的紧凑表示。因为指纹是基于空间和顺序特征而不是精确的比特序列，所以即使在压缩因素，源分辨率，开始和停止时间，帧率等之间的视频之间存在小的差异，也可以有效地比较视频的视觉内容上。可以使用比较视频指纹，例如，从视频库搜索和删除受版权保护的视频。此外，为了保存存储空间，可以检测和丢弃重复的视频。

4. 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.

5. 发明授权

US08805090B1 Matching based upon rank 有权
标题翻译：基于等级匹配
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。

6. 发明授权

US08738633B1 Transformation invariant media matching 有权
标题翻译：转换不变媒体匹配
公开(公告)号：US08738633B1
公开(公告)日：2014-05-27
申请号：US13362905
申请日：2012-01-31
申请人： Matthew Sharifi , Sergey Ioffe , Jay Yagnik , Gheorghe Postelnicu , Dominik Roblek , George Tzanetakis
发明人： Matthew Sharifi , Sergey Ioffe , Jay Yagnik , Gheorghe Postelnicu , Dominik Roblek , George Tzanetakis
IPC分类号： G06F17/30
CPC分类号： G06K9/6267 , G06F17/3002 , G06F17/30244 , G06K9/00013
摘要： This disclosure relates to transformation invariant media matching. A fingerprinting component can generate a transformation invariant identifier for media content by adaptively encoding the relative ordering of interest points in media content. The interest points can be grouped into subsets, and stretch invariant descriptors can be generated for the subsets based on ratios of coordinates of interest points included in the subsets. The stretch invariant descriptors can be aggregated into a transformation invariant identifier. An identification component compares the identifier against a set of identifiers for known media content, and the media content can be matched or identified as a function of the comparison.
摘要翻译：本公开涉及变换不变媒体匹配。指纹分量可以通过对媒体内容中的兴趣点的相对排序进行自适应编码来生成媒体内容的变换不变标识符。可以将兴趣点分组为子集，并且可以基于子集中包括的兴趣点坐标的比例为子集生成拉伸不变描述符。拉伸不变描述符可以聚合成变换不变标识符。识别部件将标识符与已知媒体内容的一组标识符进行比较，并且媒体内容可以作为比较的函数进行匹配或标识。

7. 发明授权

US08589457B1 Training scoring models optimized for highly-ranked results 有权
公开(公告)号：US08589457B1
公开(公告)日：2013-11-19
申请号：US13616108
申请日：2012-09-14
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.

8. 发明授权

US08588525B1 Transformation invariant media matching 有权
公开(公告)号：US08588525B1
公开(公告)日：2013-11-19
申请号：US13298957
申请日：2011-11-17
申请人： Jay Yagnik , Sergey Ioffe
发明人： Jay Yagnik , Sergey Ioffe
IPC分类号： G06K9/00
CPC分类号： H04N19/60 , G06K9/00744
摘要： This disclosure relates to transformation invariant media matching. A fingerprinting component can generate a transformation invariant identifier for media content by adaptively encoding the relative ordering of signal markers in media content. The signal markers can be adaptively encoded via reference point geometry, or ratio histograms. An identification component compares the identifier against a set of identifiers for known media content, and the media content can be matched or identified as a function of the comparison.

9. 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.

10. 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。

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