公开(公告)号：US08965891B1

公开(公告)日：2015-02-24

申请号：US14083043

申请日：2013-11-18

Applicant: Google Inc.

Inventor： Samy Bengio ,  Gal Chechik ,  Sergey Ioffe ,  Jay Yagnik

IPC: G06F17/30 ,  G06K9/66 ,  G06K9/62

CPC classification number: G06K9/66 ,  G06F17/30244 ,  G06F17/3053 ,  G06K9/6267 ,  Y10S707/913 ,  Y10S707/915

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US10115146B1

公开(公告)日：2018-10-30

申请号：US14688691

申请日：2015-04-16

Applicant: GOOGLE INC.

Inventor： John Roberts Anderson ,  Ryan Michael Rifkin ,  Jay Yagnik ,  Rasmus Larsen ,  Sarvjeet Singh ,  Yi-Fan Chen ,  Anandsudhakar Kesari

IPC: G06Q30/00 ,  G06Q30/06 ,  G06Q30/02

Abstract: Implementations include systems and methods for scoring candidates for set recommendation problems. An example method includes repeating, for each code in code arrays for items in a set of items, determining a most common value for the code. In some implementations, the method includes determining that the most common value occurs with a frequency that meets an occurrence threshold and adding the code and the most common value to set-inclusion criteria. In other implementations, the method includes determining a value for the code from a code array for a seed item and adding the code and the most common value to set-inclusion criteria when the value for the code from the code array for the seed item matches the most common value. The method may also include evaluating a similarity with a candidate item based on the set-inclusion criteria and basing a recommendation regarding the candidate item on the similarity.

公开(公告)号：US20170323183A1

公开(公告)日：2017-11-09

申请号：US15656192

申请日：2017-07-21

Applicant: Google Inc.

Inventor： Sudheendra Vijayanarasimhan ,  Jay Yagnik

IPC: G06K9/62 ,  G06K9/66 ,  G06N3/04 ,  G06N3/08

CPC classification number: G06K9/6267 ,  G06K9/66 ,  G06N3/04 ,  G06N3/082

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classification using a neural network. One of the methods for processing an input through each of multiple layers of a neural network to generate an output, wherein each of the multiple layers of the neural network includes a respective multiple nodes includes for a particular layer of the multiple layers: receiving, by a classification system, an activation vector as input for the particular layer, selecting one or more nodes in the particular layer using the activation vector and a hash table that maps numeric values to nodes in the particular layer, and processing the activation vector using the selected nodes to generate an output for the particular layer.

公开(公告)号：US09552511B2

公开(公告)日：2017-01-24

申请号：US14718212

申请日：2015-05-21

Applicant: Google Inc.

Inventor： Jay Yagnik

IPC: G06K9/00 ,  G06F17/30 ,  G06K9/62

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：US09445047B1

公开(公告)日：2016-09-13

申请号：US14220721

申请日：2014-03-20

Applicant: Google Inc.

Inventor： Christian Frueh ,  Krishna Bharat ,  Jay Yagnik

IPC: H04N7/14 ,  H04N7/15

CPC classification number: H04N7/15 ,  G06K9/00597 ,  G06K9/3233

Abstract: A method and system include identifying, by a processing device, at least one media clip captured by at least one camera for an event, detecting at least one human object in the at least one media clip, and calculating, by the processing device, a region in the at least one media clip containing a focus of attention of the detected human object.

Abstract translation: 方法和系统包括由处理设备识别由至少一个摄像机捕获的用于事件的至少一个媒体剪辑，检测至少一个媒体剪辑中的至少一个人物，并且由处理设备计算一个 所述至少一个媒体剪辑中的区域包含所检测到的人类对象的关注焦点。

公开(公告)号：US09087242B2

公开(公告)日：2015-07-21

申请号：US13633067

申请日：2012-10-01

Applicant: Google Inc.

Inventor： Rahul Sukthankar ,  Jay Yagnik

IPC: G06F3/0481 ,  G11B27/34 ,  G06K9/00

CPC classification number: G06K9/00744 ,  G06F17/3079 ,  G06F17/3082 ,  G06K9/00718 ,  G06T9/00

Abstract: A volume identification system identifies a set of unlabeled spatio-temporal volumes within each of a set of videos, each volume representing a distinct object or action. The volume identification system further determines, for each of the videos, a set of volume-level features characterizing the volume as a whole. In one embodiment, the features are based on a codebook and describe the temporal and spatial relationships of different codebook entries of the volume. The volume identification system uses the volume-level features, in conjunction with existing labels assigned to the videos as a whole, to label with high confidence some subset of the identified volumes, e.g., by employing consistency learning or training and application of weak volume classifiers.The labeled volumes may be used for a number of applications, such as training strong volume classifiers, improving video search (including locating individual volumes), and creating composite videos based on identified volumes.

Abstract translation: 体积识别系统识别一组视频中的每一个中的一组未标记的时空体积，每个体积表示不同的对象或动作。 音量识别系统进一步为每个视频确定表征整个音量的一组音量级特征。 在一个实施例中，特征基于码本并且描述卷的不同码本条目的时间和空间关系。 音量识别系统使用音量级特征，结合分配给整个视频的现有标签，以高度置信的方式标识所识别的体积的一些子集，例如通过采用一致性学习或训练和应用弱音量分类器 。 标记的卷可以用于许多应用，例如训练强大的分类器，改进视频搜索（包括定位各个卷），以及基于识别的卷创建复合视频。

公开(公告)号：US08847951B1

公开(公告)日：2014-09-30

申请号：US14055242

申请日：2013-10-16

Applicant: Google Inc.

Inventor： Dragomir Anguelov ,  Abhijit S. Ogale ,  Ehud Rivlin ,  Jay Yagnik

IPC: G06T15/00 ,  G09G5/377

CPC classification number: G09G5/377 ,  G06F3/1462 ,  G09G2340/12 ,  G09G2340/14 ,  G09G2354/00 ,  G09G2370/022 ,  G09G2380/00

Abstract: Methods and systems permit automatic matching of videos with images from dense image-based geographic information systems. In some embodiments, video data including image frames is accessed. The video data may be segmented to determine a first image frame of a segment of the video data. Data representing information from the first image frame may be automatically compared with data representing information from a plurality of image frames of an image-based geographic information data system. Such a comparison may, for example, involve a search for a best match between geometric features, histograms, color data, texture data, etc. of the compared images. Based on the automatic comparing, an association between the video and one or more images of the image-based geographic information data system may be generated. The association may represent a geographic correlation between selected images of the system and the video data.

Abstract translation: 方法和系统允许视频与来自基于图像的地理信息系统的图像自动匹配。 在一些实施例中，访问包括图像帧的视频数据。 视频数据可以被分割以确定视频数据的片段的第一图像帧。 表示来自第一图像帧的信息的数据可以与表示来自基于图像的地理信息数据系统的多个图像帧的信息的数据自动进行比较。 这样的比较可以例如涉及搜索比较图像的几何特征，直方图，颜色数据，纹理数据等之间的最佳匹配。 基于自动比较，可以生成视频与基于图像的地理信息数据系统的一个或多个图像之间的关联。 该关联可以表示系统的所选图像与视频数据之间的地理相关性。

公开(公告)号：US08798438B1

公开(公告)日：2014-08-05

申请号：US13708647

申请日：2012-12-07

Applicant: Google Inc.

Inventor： Jay Yagnik ,  Douglas Eck

IPC: H04N5/92

CPC classification number: H04N21/47217 ,  G11B27/034 ,  G11B27/10 ,  G11B27/28 ,  G11B27/34 ,  H04N21/233 ,  H04N21/23418 ,  H04N21/26258

Abstract: A computing system may process a plurality of audiovisual files to determine a mapping between audio characteristics and visual characteristics. The computing system may process an audio playlist to determine audio characteristics of the audio playlist. The computing system may determine, using the mapping, visual characteristics that are complementary to the audio characteristics of the audio playlist. The computing system may search a plurality of images to find one or more image(s) that have the determined visual characteristics. The computing system may link or associate the one or more image(s) that have the determined visual characteristics to the audio playlist such that the one or more images are displayed on a screen of the computing device during playback of the audio playlist.

Abstract translation: 计算系统可以处理多个视听文件以确定音频特征和视觉特征之间的映射。 计算系统可以处理音频播放列表以确定音频播放列表的音频特性。 计算系统可以使用映射来确定与音频播放列表的音频特性相互补充的视觉特征。 计算系统可以搜索多个图像以找到具有确定的视觉特征的一个或多个图像。 计算系统可以将具有确定的视觉特征的一个或多个图像链接或关联到音频播放列表，使得一个或多个图像在播放音频播放列表期间在计算设备的屏幕上显示。