公开(公告)号：US09922051B2

公开(公告)日：2018-03-20

申请号：US15225908

申请日：2016-08-02

Applicant: Yahoo! Inc.

Inventor： Jia Li ,  Nadav Golbandi ,  XianXing Zhang

IPC: G06F17/30 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06F17/30274 ,  G06F17/30253 ,  G06F17/30256 ,  G06F17/30687 ,  G06F17/30713 ,  G06K9/4642 ,  G06K9/6223 ,  G06K9/6226 ,  G06K9/6262

Abstract: Disclosed herein is a system and method that facilitate searching and/or browsing of images by clustering, or grouping, the images into a set of image clusters using facets, such as without limitation visual properties or visual characteristics, of the images, and representing each image cluster by a representative image selected for the image cluster. A map-reduce based probabilistic topic model may be used to identify one or more images belonging to each image cluster and update model parameters.

公开(公告)号：US09554030B2

公开(公告)日：2017-01-24

申请号：US14500911

申请日：2014-09-29

Applicant: Yahoo! Inc.

Inventor： Jia Li ,  Haojian Jin

IPC: H04N5/232 ,  G06K9/32

CPC classification number: H04N5/23212 ,  G06K9/3233 ,  H04N5/23216 ,  H04N5/23293

Abstract: An approach is provided for acquiring images with camera-enabled mobile devices using objects of interest recognition. A mobile device is configured to acquire an image represented by image data and process the image data to identify a plurality of candidate objects of interest in the image. The plurality of candidate objects of interest may be identified based upon a plurality of low level features or “cues” in the image data. Example cues include, without limitation, color contrast, edge density and superpixel straddling. A particular candidate object of interest is selected from the plurality of candidate objects of interest and a graphical symbol is displayed on a screen of the mobile device to identify the particular candidate object of interest. The particular candidate object of interest may be located anywhere on the image. Passive auto focusing is performed at the location of the particular candidate object of interest.

Abstract translation: 提供了一种用于使用感兴趣的对象识别摄像机的移动设备来获取图像的方法。 移动装置被配置为获取由图像数据表示的图像并处理图像数据以识别图像中的多个候选对象。 可以基于图像数据中的多个低级特征或“提示”来识别多个候选对象。 示例提示包括但不限于颜色对比度，边缘密度和超像素跨越。 从多个感兴趣的候选对象中选择特定的候选对象，并且在移动设备的屏幕上显示图形符号以识别特定的感兴趣的候选对象。 感兴趣的特定候选对象可以位于图像的任何地方。 在特定候选对象的位置执行被动自动对焦。

公开(公告)号：US09460518B2

公开(公告)日：2016-10-04

申请号：US13865142

申请日：2013-04-17

Applicant: Yahoo! Inc.

Inventor： Lyndon Kennedy ,  Jia Li ,  Ioannis Kalantidis

IPC: G06T7/00 ,  G06K9/00

CPC classification number: G06T7/0079 ,  G06K9/00369 ,  G06T7/10 ,  G06T7/70 ,  G06T2207/10024 ,  G06T2207/20021 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30196

Abstract: Techniques are provided for efficiently identifying relevant product images based on product items detected in a query image. In general, a query image may represent a digital image in any format that depicts a human body and one or more product items. For example, a query image may be an image for display on a webpage, an image captured by a user using a camera device, or an image that is part of a media content item, such as a frame from a video. Product items may be detected in a query image by segmenting the query image into a plurality of image segments and clustering one or more of the plurality image segments into one or more image segment clusters. The resulting image segments and image segment clusters may be used to search for visually similar product images.

Abstract translation: 提供了基于在查询图像中检测到的产品项目来有效地识别相关产品图像的技术。 通常，查询图像可以表示描绘人体和一个或多个产品项目的任何格式的数字图像。 例如，查询图像可以是用于在网页上显示的图像，由使用相机设备的用户捕获的图像，或作为诸如来自视频的帧的媒体内容项的一部分的图像。 可以通过将查询图像分割成多个图像片段并将多个图像片段中的一个或多个聚类成一个或多个图像片段群集来在查询图像中检测产品项目。 所得到的图像段和图像段聚类可用于搜索视觉上相似的产品图像。

公开(公告)号：US20160110794A1

公开(公告)日：2016-04-21

申请号：US14518431

申请日：2014-10-20

Applicant: YAHOO! INC.

Inventor： Jen-Hao Hsiao ,  Nan Liu ,  Jia Li

IPC: G06Q30/06 ,  G06K9/62 ,  G06N5/02

CPC classification number: G06Q30/0631 ,  G06K9/00677 ,  G06K9/6256 ,  G06K9/6277

Abstract: Disclosed herein is item recommender that uses a model trained using a combination of at least visual item similarity training data and social activity training data. The model may be used, for example, to identify a set of recommended products having similar visual features as a given product. The set of recommended products may be presented to the user along with the given product. The model may be continuously updated using feedback from users to identify the features considered to be important to the users relative to other features.

Abstract translation: 本文公开了使用使用至少视觉项目相似性训练数据和社交活动训练数据的组合训练的模型的项目推荐者。 例如，该模型可以用于识别具有与给定产品相似的视觉特征的一组推荐产品。 推荐产品的集合可以与给定的产品一起呈现给用户。 可以使用来自用户的反馈来不断更新该模型，以识别被认为对用户相对于其他特征重要的特征。

公开(公告)号：US20160005097A1

公开(公告)日：2016-01-07

申请号：US14325192

申请日：2014-07-07

Applicant: Yahoo! Inc.

Inventor： JenHao Hsiao ,  Jia Li

IPC: G06Q30/06

CPC classification number: G06Q30/0631

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate or support one or more processes and/or operations for one or more on-line recommendations, such as product-related recommendations, for example.

Abstract translation: 公开了可以全部或部分地使用一个或多个计算设备实现一个或多个在线建议的一个或多个过程和/或操作的一个或多个处理和/或操作的示例性方法，设备和/或制品 ，例如与产品相关的建议。

公开(公告)号：US20150261752A1

公开(公告)日：2015-09-17

申请号：US14215279

申请日：2014-03-17

Applicant: Yahoo! Inc.

Inventor： Jia Li ,  Joseph Kaye

IPC: G06F17/30 ,  G06F3/0482 ,  G06F3/0484

CPC classification number: G06F16/48

Abstract: Personalized criteria-based media organization is provided. Digital media items are organized into one or more albums. At least one album is associated with album membership criteria and includes only digital media items that satisfy the album membership criteria. An album is updated by receiving user input identifying at least one criteria creation element, generating user-defined album membership criteria based on the at least one criteria creation element, identifying any matching digital media items that satisfy the user-defined album membership criteria, and associating the matching digital media items with the album.

Abstract translation: 提供了个性化的基于标准的媒体组织。 数字媒体项目被组织成一个或多个相册。 至少一张专辑与专辑成员资格标准相关联，并且仅包括满足专辑成员资格标准的数字媒体项目。 通过接收标识至少一个标准创建元素的用户输入来更新相册，基于至少一个标准创建元素生成用户定义的相册成员资格标准，识别满足用户定义的相册会员资格标准的任何匹配的数字媒体项，以及 将匹配的数字媒体项目与专辑相关联。

公开(公告)号：US20150032535A1

公开(公告)日：2015-01-29

申请号：US13951078

申请日：2013-07-25

Applicant: YAHOO! INC.

Inventor： Jia Li ,  David Shamma

IPC: G06Q50/00 ,  G06Q30/02

CPC classification number: G06Q50/01 ,  G06Q30/0255

Abstract: Disclosed is a system and method for automatically detecting social relationships from consumer image collections. The disclosed systems and methods provide the ability to infer relationships between people thereby creating dynamic social networks from the occurrences of people appearing in digital images. Occurrences of people in pictures can be detected based on known or to be known facial recognition technology. These inferences enable relationship determinations regarding whether the people are family members, friends, acquaintances or merely strangers who happen to be in the same place at the same time. The disclosed detection of such relationships enables the building of intelligent image management systems. Furthermore, based on the detected social relationships, advertisements can be served not solely to a single person, but to multiple people within the scope of the social relationship

Abstract translation: 公开了一种用于从消费者图像集合自动检测社会关系的系统和方法。 所公开的系统和方法提供了推断人之间的关系的能力，从而创建出现在数字图像中出现的人的动态社交网络。 可以基于已知或已知的面部识别技术来检测图片中的人的出现。 这些推论能够确定人们是否是家庭成员，朋友，熟人，或者只是同时处于同一地点的陌生人。 披露的这种关系的检测使得能够构建智能图像管理系统。 此外，根据检测到的社会关系，广告不仅可以服务于一个人，而且可以在社会关系范围内的多个人

公开(公告)号：US09720882B2

公开(公告)日：2017-08-01

申请号：US14548852

申请日：2014-11-20

Applicant: YAHOO! INC.

Inventor： Bin Ni ,  Jia Li

IPC: G09G5/00 ,  G06F17/21 ,  G06T3/40 ,  G06F17/30

CPC classification number: G06F17/211 ,  G06F17/30719 ,  G06T3/40

Abstract: Generating notifications comprising text and image data for client devices with limited display screens is disclosed. An image to be included in the notification is resized and reshaped using image processing techniques. The resized image is further analyzed to identify optimal portions for placing the text data. The text data can also be analyzed and shortened for including at the identified portion of resized image to generate a notification. The resulting notification displays the text and image data optimally within the limited screen space of the client device so that a user observing the notification can obtain the information at a glance.

公开(公告)号：US20160342623A1

公开(公告)日：2016-11-24

申请号：US14715246

申请日：2015-05-18

Applicant: Yahoo! Inc.

Inventor： JenHao Hsiao ,  Jia Li

IPC: G06F17/30

CPC classification number: G06F16/583

Abstract: An approach for performing mobile visual search uses deep variant coding of images to reduce the amount of data transmitted from mobile devices to a search server and to provide more efficient indexing and searching on the search server. The amount of data used to represent an image varies depending upon the content of the image and is less than conventional fixed bit length hashing approaches. Denser regions of a feature space are represented by more encoding bits and sparser regions of the feature space are represented by fewer encoding bits, so that the overall number of encoding bits for an image feature is reduced. The approach generally involves determining a set of hash functions that provide deep hashing with more evenly-distributed hash buckets. One or more additional hash functions may be selectively generated for particular hash buckets that contain more than a specified number of images.

Abstract translation: 用于执行移动视觉搜索的方法使用图像的深度变体编码来减少从移动设备传输到搜索服务器的数据量，并在搜索服务器上提供更有效的索引和搜索。 用于表示图像的数据量根据图像的内容而变化，并且小于常规固定位长度哈希方法。 特征空间的密集区域由更多的编码比特表示，并且特征空间的稀疏区域由较少的编码比特表示，使得图像特征的编码比特的总数减少。 该方法通常涉及确定一组哈希函数，它们使用更均匀分布的哈希桶来提供深度哈希。 可以针对包含多于指定数目的图像的特定哈希桶选择性地生成一个或多个附加散列函数。

公开(公告)号：US20160267637A1

公开(公告)日：2016-09-15

申请号：US14656390

申请日：2015-03-12

Applicant: YAHOO! INC.

Inventor： Jenhao Hsiao ,  Jia Li

IPC: G06T7/00 ,  G06F17/30 ,  G06K9/62 ,  G06Q30/02

CPC classification number: G06F16/24578 ,  G06F16/56 ,  G06F16/5854 ,  G06F16/951 ,  G06K9/00624 ,  G06K9/4628 ,  G06K9/6271 ,  G06Q30/0256

Abstract: Disclosed are systems and methods for improving interactions with and between computers in a search system supported by or configured with search servers or platforms. The systems interact to identify and retrieve data across platforms, which data can be used to improve the quality of results data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide a Deep Fast Search (DFS) that improves content search accuracy that executes independent of the search database, while achieving an increased content retrieval speed. The disclosed systems and methods employ two complementary deep feature searches: 1) a coarse deep feature search and a 2) fine deep feature search. Thus, the disclosed systems and methods employ a coarse-to-fine strategy that embodies the efficiency and cost effectiveness of the coarse deep feature search and the accuracy of the fine deep feature search.

Abstract translation: 公开了用于改善由搜索服务器或平台支持或配置的搜索系统中的计算机之间的交互作用的系统和方法。 系统进行交互以识别和检索跨平台的数据，哪些数据可用于提高用于处理这些系统中处理器之间的交互的结果数据的质量。 所公开的系统和方法提供深度快速搜索（DFS），其提高独立于搜索数据库执行的内容搜索精度，同时实现增加的内容检索速度。 所公开的系统和方法采用两个互补的深度特征搜索：1）粗略的深度特征搜索和2）精细深度特征搜索。 因此，所公开的系统和方法采用粗略到精细的策略，其体现粗略特征搜索的效率和成本效益以及精细深度特征搜索的准确性。