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1. 发明授权

US09311403B1 Hashing techniques for data set similarity determination 有权
标题翻译：数据集相似性确定的哈希技术
公开(公告)号：US09311403B1
公开(公告)日：2016-04-12
申请号：US13162061
申请日：2011-06-16
申请人： Sergey Ioffe
发明人： Sergey Ioffe
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06F17/30247 , G06F17/30256
摘要： Methods, systems and computer program product embodiments for hashing techniques for determining similarity between data sets are described herein. A method embodiment includes, initializing a random number generator with a weighted min-hash value as a seed, wherein the weighted min-hash value approximates a similarity distance between data sets. A number of bits in the weighted min-hash value is determined by uniformly sampling an integer bit value using the random number generator. A system embodiment includes a repository configured to store a plurality of data sets and a hash generator configured to generate weighted min-hash values from the data sets. The system further includes a similarity determiner configured to determine a similarity between the data sets.
摘要翻译：本文描述了用于确定数据集之间的相似性的散列技术的方法，系统和计算机程序产品实施例。方法实施例包括：初始化具有加权最小哈希值作为种子的随机数发生器，其中加权最小哈希值近似数据集之间的相似距离。通过使用随机数发生器对整数位值进行均匀采样来确定加权最小哈希值中的多个位。系统实施例包括被配置为存储多个数据集的存储库和被配置为从数据集生成加权最小散列值的散列生成器。该系统还包括被配置为确定数据集之间的相似性的相似性确定器。

2. 发明授权

US08983941B1 Visual content retrieval 有权
公开(公告)号：US08983941B1
公开(公告)日：2015-03-17
申请号：US13621039
申请日：2012-09-15
申请人： Erik Murphy-Chutorian , Charles J. Rosenberg , Nemanja Petrovic , Sergey Ioffe , Sean O'Malley
发明人： Erik Murphy-Chutorian , Charles J. Rosenberg , Nemanja Petrovic , Sergey Ioffe , Sean O'Malley
IPC分类号： G06F17/30
CPC分类号： G06K9/46 , G06F17/30247 , G06F17/30265
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating image search results. One of the methods includes receiving first image search results responsive to a text query, each first image search result associated with a respective first score indicating a relevance of an image represented by the first image search result to the text query. Second image search results responsive to a query image are received, each second image search result associated with a respective second score indicating a measure of similarity between an image represented by the second image search result and the query image. A set of final image search results is selected including combining first scores and second scores of the selected first image search results. The final image search results are ordered by similarity to the query image.

3. 发明授权

US08880899B1 Systems and methods for facilitating flip-resistant media fingerprinting 有权
标题翻译：用于促进反转媒体指纹识别的系统和方法
公开(公告)号：US08880899B1
公开(公告)日：2014-11-04
申请号：US13457472
申请日：2012-04-26
申请人： Sergey Ioffe
发明人： Sergey Ioffe
IPC分类号： G06F11/30
CPC分类号： G06F17/3033 , G06F17/3002 , G06F17/30047
摘要： 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.
摘要翻译：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。

4. 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。

5. 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.

6. 发明授权

US08509499B2 Automatic face detection and identity masking in images, and applications thereof 有权
公开(公告)号：US08509499B2
公开(公告)日：2013-08-13
申请号：US13302634
申请日：2011-11-22
申请人： Sergey Ioffe , Lance Williams , Dennis Strelow , Andrea Frome , Luc Vincent
发明人： Sergey Ioffe , Lance Williams , Dennis Strelow , Andrea Frome , Luc Vincent
IPC分类号： G06K9/36
CPC分类号： G06T11/001 , G06K9/00281 , G06T5/005
摘要： A method and system of identity masking to obscure identities corresponding to face regions in an image is disclosed. A face detector is applied to detect a set of possible face regions in the image. Then an identity masker is used to process the detected face regions by identity masking techniques in order to obscure identities corresponding to the regions. For example, a detected face region can be blurred as if it is in motion by a motion blur algorithm, such that the blurred region can not be recognized as the original identity. Or the detected face region can be replaced by a substitute facial image by a face replacement algorithm to obscure the corresponding identity.

7. 发明申请

US20130204905A1 REMAPPING LOCALITY-SENSITIVE HASH VECTORS TO COMPACT BIT VECTORS 审中-公开
标题翻译：重新定位敏感的HASH矢量来压缩位图矢量
公开(公告)号：US20130204905A1
公开(公告)日：2013-08-08
申请号：US13368193
申请日：2012-02-07
申请人： Sergey Ioffe
发明人： Sergey Ioffe
IPC分类号： G06F17/30
CPC分类号： H04L9/3236 , H04L9/00
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a hash vector r, a vector of locality-sensitive hash values, each hash value being an element of the hash vector r, each element having an index position; and generating a compact vector v corresponding to the hash vector r, wherein the compact vector v is a vector of compact elements each having an index position, wherein each compact element corresponds to the element of the hash vector r having the same index position, and wherein each compact element is a b-bit integer selected from the set of all b-bit integers {0, 1, . . . , 2b−1} based on the corresponding hash element.
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接收散列向量r的计算机程序，位置敏感哈希值的向量，每个哈希值是散列向量r的元素，每个元素具有索引位置; 并产生对应于散列向量r的紧凑向量v，其中紧凑向量v是每个具有索引位置的紧凑元素的向量，其中每个紧凑元素对应于具有相同索引位置的散列向量r的元素，以及其中每个紧凑元素是从所有b位整数{0,1，...的集合中选择的b位整数。。。，2b-1}基于相应的散列元素。

8. 发明授权

US07684594B2 Method and apparatus for estimating object part location in digital image data using feature value analysis 有权
标题翻译：使用特征值分析来估计数字图像数据中的物体部分位置的方法和装置
公开(公告)号：US07684594B2
公开(公告)日：2010-03-23
申请号：US11349202
申请日：2006-02-08
申请人： Sergey Ioffe
发明人： Sergey Ioffe
IPC分类号： G06K9/46 , G06T7/00
CPC分类号： G06K9/00248
摘要： A method and an apparatus estimate an object part location in a digital image using feature value analysis. The method according to one embodiment accesses digital image data representing a region including an object part of a digital image; accesses reference data including class data of classes relating to predetermined positions of the object part in predetermined regions, and features that discriminate among the classes; calculates feature values for the features in the region using pixel values within the region; and determines a location estimate of the object part using the feature values and the reference data.
摘要翻译：方法和装置使用特征值分析来估计数字图像中的对象部分位置。根据一个实施例的方法访问表示包括数字图像的对象部分的区域的数字图像数据; 访问包括与预定区域中的对象部分的预定位置相关的类别的类数据的参考数据，以及区分类别的特征; 使用区域内的像素值计算区域中的要素的特征值; 并且使用特征值和参考数据确定对象部分的位置估计。

9. 发明授权

US07596247B2 Method and apparatus for object recognition using probability models 失效
标题翻译：使用概率模型对象识别的方法和装置
公开(公告)号：US07596247B2
公开(公告)日：2009-09-29
申请号：US10734258
申请日：2003-12-15
申请人： Sergey Ioffe
发明人： Sergey Ioffe
IPC分类号： G06K9/00
CPC分类号： G06K9/6296 , G06K9/00281
摘要： A method and an apparatus automatically recognize or verify objects in a digital image using probability models. According to a first aspect, a method and apparatus automatically recognize or verify objects in a digital image by: accessing digital image data including an object of interest therein; detecting an object of interest in the image; normalizing the object to generate a normalized object representation; extracting a plurality of features from the normalized object representation; and applying each feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class. In one embodiment, the previously-determined additive probability model is an Additive Gaussian Model.
摘要翻译：方法和装置使用概率模型自动识别或验证数字图像中的对象。根据第一方面，一种方法和装置通过以下方式自动识别或验证数字图像中的对象：访问包括其中的关注对象的数字图像数据; 检测图像中感兴趣的对象; 规范化对象以生成规范化对象表示; 从归一化对象表示中提取多个特征; 以及将每个特征应用于先前确定的附加概率模型以确定感兴趣对象属于现有类的可能性。在一个实施例中，先前确定的附加概率模型是加性高斯模型。

10. 发明申请

US20150169633A1 RANKING OVER HASHES 有权
标题翻译：排名靠前
公开(公告)号：US20150169633A1
公开(公告)日：2015-06-18
申请号：US13040168
申请日：2011-03-03
申请人： Yangli Hector Yee , Sergey Ioffe , Samy Bengio
发明人： Yangli Hector Yee , Sergey Ioffe , Samy Bengio
IPC分类号： G06F17/30
CPC分类号： G06F17/30247 , G06F17/3028
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image ranking model to rank images based on hashes of their contents using a lookup table. An image training set is received. An image ranking model is trained with the training set by generating an image hash for each image of the ordered pair of images based on one or more features extracted from the image, computing a first score for a first image hash of a first image of the pair and a second score for a second image hash of a second image of the pair using the image ranking model, determining whether to update the image ranking model based on the first score and the second score, and updating the image ranking model using an update value based on the first score and the second score.
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，用于训练图像排序模型以使用查找表基于其内容的散列来对图像进行排序。接收图像训练集。基于从图像提取的一个或多个特征，通过为所述有序对图像的每个图像生成图像散列来训练图像排序模型，所述图像排序模型通过针对所述图像的第一图像的第一图像散列计算第一分数，并且使用所述图像排序模型对所述对的第二图像的第二图像散列进行第二分数，基于所述第一分数和所述第二分数来确定是否更新所述图像排序模型，以及使用更新来更新所述图像排名模型基于第一分和第二分的价值。

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