公开(公告)号：US09684715B1

公开(公告)日：2017-06-20

申请号：US13415704

申请日：2012-03-08

Applicant: David Ross ,  Jay Yagnik

Inventor： David Ross ,  Jay Yagnik

IPC: G06F17/30 ,  G06F17/00

CPC classification number: G06F17/30743 ,  G06F17/00 ,  G06F17/3074

Abstract: 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

Applicant: Jay Yagnik ,  Sergey Ioffe

Inventor： Jay Yagnik ,  Sergey Ioffe

IPC: G06K9/68

CPC classification number: G06K9/6212

Abstract: 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.

Abstract translation: 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

Applicant: Michele Covell ,  Jay Yagnik ,  Jeff Faust ,  Shumeet Baluja

Inventor： Michele Covell ,  Jay Yagnik ,  Jeff Faust ,  Shumeet Baluja

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

CPC classification number: G06K9/00758 ,  G06F17/30784

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US08180667B1

公开(公告)日：2012-05-15

申请号：US12132576

申请日：2008-06-03

Applicant: Shumeet Baluja ,  Yushi Jing ,  Thomas Leung ,  Jay Yagnik

Inventor： Shumeet Baluja ,  Yushi Jing ,  Thomas Leung ,  Jay Yagnik

IPC: G06Q40/00

CPC classification number: G06Q30/0217 ,  G06K9/00744 ,  G06Q40/12 ,  H04N21/23418 ,  H04N21/2743 ,  H04N21/812

Abstract: A video hosting service automatically identifies, in a video database, a set of videos associated with an advertiser, and presents the identified videos to the advertiser for consideration. The videos may be selected based on analysis of their video content for images of logos associated with the advertisers. The video hosting service may then receive from the advertisers a listing of which of the presented videos should be given an award.

Abstract translation: 视频托管服务在视频数据库中自动识别与广告商相关联的一组视频，并将识别的视频呈现给广告商以供考虑。 可以基于对与广告商相关联的徽标的图像的视频内容的分析来选择视频。 然后，视频托管服务可以从广告商接收应该给出哪个被呈现的视频的列表。

公开(公告)号：US08145679B1

公开(公告)日：2012-03-27

申请号：US12966747

申请日：2010-12-13

Applicant: Shumeet Baluja ,  Yushi Jing ,  Dandapani Sivakumar ,  Jay Yagnik

Inventor： Shumeet Baluja ,  Yushi Jing ,  Dandapani Sivakumar ,  Jay Yagnik

IPC: G06F17/30

CPC classification number: G06F17/30035 ,  G06F17/30828 ,  G06Q30/02 ,  Y10S707/99942 ,  Y10S707/99945

Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes inferring labels for videos, users, advertisements, groups of users, and other entities included in a social network system. The inferred labels can be used to generate recommendations such as videos or advertisements in which a user may be interested. Inferred labels can be generated based on social or other relationships derived from, for example, profiles or activities of social network users. Inferred labels can be advantageous when explicit information about these entities is not available. For example, a particular user may not have clicked on any online advertisements, so the user is not explicitly linked to any advertisements.

公开(公告)号：US08055664B2

公开(公告)日：2011-11-08

申请号：US11742995

申请日：2007-05-01

Applicant: Shumeet Baluja ,  Yushi Jing ,  Dandapani Sivakumar ,  Jay Yagnik

Inventor： Shumeet Baluja ,  Yushi Jing ,  Dandapani Sivakumar ,  Jay Yagnik

IPC: G06F17/30 ,  G06Q30/00

CPC classification number: G06N5/02 ,  G06N99/005 ,  G06Q30/0274

Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes determining, for a portion of users of a social network, label values each comprising an inferred interest level of a user in a subject indicated by a label, associating a first user with one or more second users based on one or more relationships specified by the first user, and outputting a first label value for the first user based on one or more second label values of the one or more second users.

Abstract translation: 本说明书的主题可以包括一种方法，其包括为社交网络的用户的一部分确定每个包括由标签指示的对象中的用户的推定的兴趣级别的标签值， 基于由第一用户指定的一个或多个关系将第一用户与一个或多个第二用户相关联，并且基于一个或多个第二用户的一个或多个第二标签值输出第一用户的第一标签值。

公开(公告)号：US08019702B1

公开(公告)日：2011-09-13

申请号：US12248784

申请日：2008-10-09

Applicant: Ullas Gargi ,  Jay Yagnik

Inventor： Ullas Gargi ,  Jay Yagnik

IPC: G06F11/00

CPC classification number: G06K9/00523

Abstract: A method, a system and a computer program product generate a statistical classification model used by a computer system to determine a class associated with an unlabeled time series event.

Abstract translation: 方法，系统和计算机程序产品生成计算机系统使用的统计分类模型来确定与未标记的时间序列事件相关联的类别。

公开(公告)号：US09054876B1

公开(公告)日：2015-06-09

申请号：US13314294

申请日：2011-12-08

Applicant: Jay Yagnik

Inventor： Jay Yagnik

IPC: G06F17/00 ,  H04L9/32

CPC classification number: G06F17/3033 ,  G06F17/30309 ,  G06K9/4676 ,  H04L9/3236

Abstract: The disclosed embodiments describe a method, an apparatus, an application specific integrated circuit, and a server that provides a fast and efficient look up for data analysis. The apparatus and server may be configured to obtain data segments from a plurality of input devices. The data segments may be individual unique subsets of the entire data set obtained by a plurality input devices. A hash function may be applied to an aggregated set of the data segments. A result of the hash function may be stored in a data structure. A codebook may be generated from the hash function results.

Abstract translation: 所公开的实施例描述了提供快速和有效地查找数据分析的方法，装置，专用集成电路和服务器。 设备和服务器可以被配置为从多个输入设备获取数据段。 数据段可以是由多个输入设备获得的整个数据集的独立子集。 哈希函数可以应用于数据段的聚合集合。 散列函数的结果可以存储在数据结构中。 可以从散列函数结果生成码本。

公开(公告)号：US09053357B2

公开(公告)日：2015-06-09

申请号：US13324058

申请日：2011-12-13

Applicant: Jay Yagnik

Inventor： Jay Yagnik

IPC: G06K9/46 ,  G06K9/00 ,  G06F17/30

CPC classification number: G06K9/00288 ,  G06F17/30247 ,  G06F17/30256 ,  G06K9/6256

Abstract: A method includes identifying a named entity, retrieving images associated with the named entity, and using a face detection algorithm to perform face detection on the retrieved images to detect faces in the retrieved images. At least one representative face image from the retrieved images is identified, and the representative face image is used to identify one or more additional images representing the at least one named entity.

Abstract translation: 一种方法包括识别命名实体，检索与命名实体相关联的图像，以及使用面部检测算法对检索到的图像执行面部检测，以检测检索到的图像中的面部。 识别来自检索到的图像的至少一个代表性面部图像，并且使用代表性面部图像来识别表示至少一个命名实体的一个或多个附加图像。

公开(公告)号：US08959128B1

公开(公告)日：2015-02-17

申请号：US13297709

申请日：2011-11-16

Applicant: Dennis Strelow ,  Jay Yagnik

Inventor： Dennis Strelow ,  Jay Yagnik

IPC: G06F7/38

CPC classification number: G06F17/16 ,  G06F17/11 ,  G06T7/246 ,  G06T7/70 ,  G06T7/73 ,  G06T2207/10016 ,  G06T2207/30244

Abstract: Wiberg minimization operates on a system with two sets of variables described by a linear function and in which some data or observations are missing. The disclosure generalizes Wiberg minimization, solving for a function that is nonlinear in both sets of variables, U and V, iteratively. In one embodiment, defining a first function ƒ(U, V) that may be defined that may be nonlinear in both a first set of variables U and a second set of variables V. A first function ƒ(U, V) may be transformed into ƒ(U, V(U)). First assumed values of the first set of variables U may be assigned. The second set of variables V may be iteratively estimated based upon the transformed first function ƒ(U, V(U)) and the assumed values of the first set of variables U such that ƒ(U, V(U)) may be minimized with respect to V. New estimates of the first set of variables U may be iteratively computed.

Abstract translation: Wiberg最小化操作在具有由线性函数描述的两组变量的系统中，其中缺少一些数据或观察值。 本公开概括了Wiberg最小化，迭代地求解了两组变量U和V中的非线性函数。 在一个实施例中，定义可以被定义为在第一变量集U和第二组变量V中都可以是非线性的第一函数ƒ（U，V）。可以变换第一函数ƒ（U，V） 进入ƒ（U，V（U））。 可以分配第一组变量U的第一假设值。 可以基于变换的第一函数ƒ（U，V（U））和第一变量集合U的假定值来迭代地估计第二组变量V，使得ƒ（U，V（U））可以被最小化 可以迭代地计算第一组变量U的新估计。