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    SELECTIVE DEGRADATION OF VIDEOS CONTAINING THIRD-PARTY CONTENT
    22.
    发明申请
    SELECTIVE DEGRADATION OF VIDEOS CONTAINING THIRD-PARTY CONTENT 有权
    包含第三方内容的视频的选择性降解

    公开(公告)号：US20170078718A1

    公开(公告)日：2017-03-16

    申请号：US14853411

    申请日：2015-09-14

    Applicant: Google Inc.

    Inventor： Sergey Ioffe

    IPC: H04N21/2343 ,  H04N21/233 ,  H04N21/2743 ,  H04N21/234

    CPC classification number: H04N21/23439 ,  H04N21/2335 ,  H04N21/23418 ,  H04N21/234345 ,  H04N21/2743 ,  H04N21/8355 ,  H04N21/8456

    Abstract: A video server receives an uploaded video and determines whether the video contains third-party content and which portions of the uploaded video match third-party content. The video server determines whether to degrade the matching portions and/or how (e.g., extent, type) to do so. The video server separates the matching portion from original portions in the uploaded video and generates a degraded version of the matching content by applying an effect such as compression, edge distortion, temporal distortion, noise addition, color distortion, or audio distortion. The video server combines the degraded portions with the original portions to output a degraded version of the uploaded video. The video server stores and/or distributes the degraded version of the uploaded video. The video server may offer the uploading user licensing terms with the content owner that the user may accept to reverse the degradation.

    Abstract translation: 视频服务器接收上传的视频并确定视频是否包含第三方内容，以及上传的视频的哪些部分与第三方内容匹配。 视频服务器确定是否降低匹配部分和/或如何（例如，范围，类型）这样做。 视频服务器将匹配部分与上传视频中的原始部分分离，并通过应用诸如压缩，边缘失真，时间失真，噪声添加，颜色失真或音频失真的效果来产生匹配内容的劣化版本。 视频服务器将劣化的部分与原始部分组合，以输出上传的视频的降级版本。 视频服务器存储和/或分发已上传视频的劣化版本。 视频服务器可以向用户可以接受的内容所有者提供上传用户许可条款以逆转劣化。

    Systems and methods for facilitating flip-resistant media fingerprinting
    23.
    发明授权
    Systems and methods for facilitating flip-resistant media fingerprinting 有权
    用于促进反转媒体指纹识别的系统和方法

    公开(公告)号：US09501510B1

    公开(公告)日：2016-11-22

    申请号：US14496983

    申请日：2014-09-25

    Applicant: Google Inc.

    Inventor： Sergey Ioffe

    IPC: G06F11/30 ,  G06F17/30 ,  G06F12/14

    CPC classification number: G06F17/3033 ,  G06F17/3002 ,  G06F17/30047

    Abstract: Systems and methods for facilitating media fingerprinting are provided. In one aspect, a system can include: a memory, a microprocessor, a communication component that receives media; and a media fingerprinting component that fingerprints the media. The media fingerprinting component employs a fingerprint generation component stored in the memory and includes: a first hash generation component that generates sets of hashes corresponding to versions of the media; and a second hash generation component that computes a final hash based, at least, on hashing the sets of hashes. In some aspects, the media fingerprinting component can generate a flip-resistant fingerprint based, at least, on the final hash. In some aspects, the flip-resistant fingerprint is the final hash.

    Abstract translation: 提供了便于媒体指纹识别的系统和方法。 在一个方面，系统可以包括：存储器，微处理器，接收介质的通信组件; 以及指纹媒体的媒体指纹识别组件。 媒体指纹分析采用存储在存储器中的指纹生成组件，包括：生成与媒体版本对应的散列集合的第一散列生成组件; 以及第二散列生成组件，其至少基于散列所述散列集合来计算最终散列。 在一些方面，媒体指纹分量可以至少在最终散列上产生一种防跳转指纹。 在某些方面，防撞指纹是最终的散列。

    Sublinear time classification via feature padding and hashing
    24.
    发明授权
    Sublinear time classification via feature padding and hashing 有权
    通过特征填充和散列进行子线性时间分类

    公开(公告)号：US09286549B1

    公开(公告)日：2016-03-15

    申请号：US13941812

    申请日：2013-07-15

    Applicant: Google Inc.

    Inventor： Sergey Ioffe ,  Alexander Toshkov Toshev

    IPC: G06K9/68 ,  G06K9/70 ,  G06K9/62

    CPC classification number: G06K9/6276 ,  G06K9/6215 ,  G06K9/6267 ,  G06K9/628

    Abstract: A linear function describing a framework for identifying an object of class k in an image sample x may be described by: wk*x+bk, where bk is the bias term. The higher the value obtained for a particular classifier, the better the match or strength of identity. A method is disclosed for classifier and/or content padding to convert dot-products to distances, applying a hashing and/or nearest neighbor technique on the resulting padded vectors, and preprocessing that may improve the hash entropy. A vector for an image, an audio, and/or a video may be received. One or more classifier vectors may be obtained. A padded image, video, and/or audio vector and classifier vector may be generated. A dot product may be approximated and a hashing and/or nearest neighbor technique may be performed on the approximated dot product to identify at least one class (or object) present in the image, video, and/or audio.

    Abstract translation: 描述用于识别图像样本x中的类k的对象的框架的线性函数可以由以下描述：wk * x + bk，其中bk是偏差项。 特定分类器获得的值越高，身份的匹配或强度越好。 公开了一种用于分类器和/或内容填充以将点产品转换为距离的方法，在所得到的填充向量上应用散列和/或最近邻技术，以及可以改善散列熵的预处理。 可以接收用于图像，音频和/或视频的向量。 可以获得一个或多个分类器向量。 可以生成填充图像，视频和/或音频向量和分类器向量。 可以近似点积，并且可以在近似点积上执行散列和/或最近邻技术，以识别存在于图像，视频和/或音频中的至少一个类（或对象）。

    Systems and methods for facilitating video fingerprinting using local descriptors
    25.
    发明授权
    Systems and methods for facilitating video fingerprinting using local descriptors 有权
    使用局部描述符促进视频指纹识别的系统和方法

    公开(公告)号：US09177350B1

    公开(公告)日：2015-11-03

    申请号：US14154969

    申请日：2014-01-14

    Applicant: Google Inc.

    Inventor： Sergey Ioffe

    IPC: G06K9/00 ,  G06T1/00

    CPC classification number: G06T1/0021 ,  G06K9/00744 ,  G06K9/4671 ,  H04N21/835

    Abstract: Systems and methods for facilitating video fingerprinting are provided. In one embodiment, a system can include: a memory, a microprocessor, a communication component that receives a video, and a video fingerprinting component that fingerprints the video with a subfingerprint (SFP). The video fingerprinting component can employ an SFP component stored in the memory and that comprises: a feature extraction component that determines local descriptors for at least one frame of a video; and a quantization component that quantizes the local descriptors to generate first frame information including a set of values for the at least one frame. The SFP component can also include: an accumulation component that accumulates first frame information over a snippet of the video; and an SFP generation component that computes the SFP associated with the snippet. The SFP can be computed based on a hash based on the accumulated first frame information over the snippet.

    Abstract translation: 提供了便于视频指纹识别的系统和方法。 在一个实施例中，系统可以包括：存储器，微处理器，接收视频的通信组件以及使用子指纹（Sff）对视频进行指纹的视频指纹分量。 视频指纹分量可以采用存储在存储器中的SFP组件，其包括：特征提取组件，其确定视频的至少一帧的本地描述符; 以及量化分量，其量化所述局部描述符以产生包括所述至少一个帧的一组值的第一帧信息。 SFP组件还可以包括：累积部件，其通过视频的片段累积第一帧信息; 以及计算与代码片段相关联的SFP的SFP生成组件。 可以基于基于片段上累积的第一帧信息的散列来计算SFP。

    Performing image similarity operations using semantic classification
    26.
    发明授权
    Performing image similarity operations using semantic classification 有权
    使用语义分类来执行图像相似度运算

    公开(公告)号：US09025811B1

    公开(公告)日：2015-05-05

    申请号：US13732813

    申请日：2013-01-02

    Applicant: Google Inc.

    Inventor： Sergey Ioffe ,  Yushi Jing ,  Stephen Holiday

    IPC: G06K9/00 ,  G06K9/62

    CPC classification number: G06F17/3025 ,  G06F17/30256 ,  G06K9/00684 ,  G06K9/62 ,  G06K9/6212 ,  G06K9/6262

    Abstract: Image similarity operations are performed in which a seed image is analyzed, and a set of semantic classifications are determined from analyzing the seed image. The set of semantic classifications can include multiple positive semantic classifications. A distance measure is determined that is specific to the set of semantic classifications. The seed image is compared to a collection of images using the distance measure. A set of similar images is determined from comparing the seed image to the collection of images.

    Abstract translation: 执行图像相似度操作，其中分析种子图像，并且通过分析种子图像来确定一组语义分类。 语义分类集合可以包括多个正的语义分类。 确定特定于语义分类集合的距离度量。 使用距离测量将种子图像与图像的集合进行比较。 通过比较种子图像和图像的集合来确定一组相似的图像。

    IMAGE DENOISING SYSTEM AND METHOD
    27.
    发明申请
    IMAGE DENOISING SYSTEM AND METHOD 有权
    图像吸收系统和方法

    公开(公告)号：US20140119664A1

    公开(公告)日：2014-05-01

    申请号：US13665449

    申请日：2012-10-31

    Applicant: Google Inc.

    Inventor： Sergey Ioffe ,  Troy Chinen ,  Vivek Kwatra ,  Hui Fang ,  Yichang Shih

    IPC: G06K9/40

    CPC classification number: G06T5/002 ,  G06K9/00221 ,  G06K9/00261 ,  G06K9/40 ,  G06T5/005 ,  G06T5/20 ,  G06T5/50 ,  G06T2207/10004 ,  G06T2207/10016 ,  G06T2207/20028 ,  G06T2207/20182 ,  G06T2207/20216 ,  G06T2207/30201

    Abstract: A method, computer program product, and computer system for identifying a first portion of a facial image in a first image, wherein the first portion includes noise. A corresponding portion of the facial image is identified in a second image, wherein the corresponding portion includes less noise than the first portion. One or more filter parameters of the first portion are determined based upon, at least in part, the first portion and the corresponding portion. At least a portion of the noise from the first portion is smoothed based upon, at least in part, the one or more filter parameters. At least a portion of face specific details from the corresponding portion is added to the first portion.

    Abstract translation: 一种用于识别第一图像中的面部图像的第一部分的方法，计算机程序产品和计算机系统，其中所述第一部分包括噪声。 面部图像的相应部分在第二图像中被识别，其中对应部分包括比第一部分少的噪声。 至少部分地基于第一部分和对应部分来确定第一部分的一个或多个过滤器参数。 至少部分地基于一个或多个过滤器参数来平滑来自第一部分的噪声的至少一部分。 来自相应部分的面部特定细节的至少一部分被添加到第一部分。

    System and method for grouping related photographs
    29.
    发明授权
    System and method for grouping related photographs 有权
    用于分组相关照片的系统和方法

    公开(公告)号：US09311310B2

    公开(公告)日：2016-04-12

    申请号：US13661425

    申请日：2012-10-26

    Applicant: GOOGLE INC.

    Inventor： Sergey Ioffe ,  Vivek Kwatra ,  Matthias Grundmann

    IPC: G09G5/00 ,  G06F17/30

    CPC classification number: G06F3/0481 ,  G06F17/30056 ,  G06F17/30265

    Abstract: A computer-implemented method, computer program product, and computing system is provided for interacting with images having similar content. In an embodiment, a method may include identifying a plurality of photographs as including a common characteristic. The method may also include generating a flipbook media item including the plurality of photographs. The method may further include associating one or more interactive control features with the flipbook media item.

    Abstract translation: 提供了计算机实现的方法，计算机程序产品和计算系统，用于与具有相似内容的图像进行交互。 在一个实施例中，方法可以包括将多个照片识别为包括共同特征。 该方法还可以包括生成包括多张照片的翻页媒体项目。 该方法可以进一步包括将一个或多个交互式控制特征与翻录媒体项目相关联。

    Systems and methods facilitating random number generation for hashes in video and audio applications
    30.
    发明授权
    Systems and methods facilitating random number generation for hashes in video and audio applications 有权
    促进随机数生成的系统和方法，用于视频和音频应用中的散列

    公开(公告)号：US09092859B1

    公开(公告)日：2015-07-28

    申请号：US14281463

    申请日：2014-05-19

    Applicant: Google Inc.

    Inventor： Sergey Ioffe

    IPC: G06K9/00 ,  G06T1/00 ,  B42D15/00 ,  G06F7/00

    CPC classification number: G06T1/0021 ,  G06F7/00 ,  G06F7/58 ,  G06F17/30 ,  G06K9/00 ,  G10L19/00 ,  G10L25/54 ,  H04L9/3239

    Abstract: Systems and methods facilitating random number generation of hashes for video and/or audio are provided. In one embodiment, a system can include: a memory, and a microprocessor that executes computer executable components. The components can include a weighted distribution generation component that can generate a sampling distribution of a weighted combination of uniform distributions, and obtain a sample value from the sampling distribution. In one embodiment, horizontal regions of substantially equal area can be identified. The sample value can be obtained by selecting one of the horizontal regions, and uniformly selecting a coordinate from the horizontal region. The coordinate can correspond to a value on a horizontal axis of the sampling distribution, and the value can be equal to a sample value. The sample value can be employed to compute a hash employed in video and/or audio fingerprinting and/or in computing image descriptors for video.

    Abstract translation: 提供了促进用于视频和/或音频的哈希的随机数生成的系统和方法。 在一个实施例中，系统可以包括：存储器和执行计算机可执行组件的微处理器。 组件可以包括加权分布生成组件，其可以生成均匀分布的加权组合的采样分布，并且从采样分布获得样本值。 在一个实施例中，可以识别基本相等面积的水平区域。 可以通过选择水平区域之一并且从水平区域均匀地选择坐标来获得采样值。 坐标可以对应于采样分布的水平轴上的值，并且该值可以等于采样值。 可以采用采样值来计算在视频和/或音频指纹中使用的散列和/或计算用于视频的图像描述符。

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