Hierarchical Sparse Representation For Image Retrieval
    1.
    发明申请
    Hierarchical Sparse Representation For Image Retrieval 有权
    图像检索的分层稀疏表示法

    公开(公告)号:US20120114248A1

    公开(公告)日:2012-05-10

    申请号:US12943805

    申请日:2010-11-10

    IPC分类号: G06K9/46

    CPC分类号: G06F17/30256

    摘要: A hierarchical sparse codebook allows efficient search and comparison of images in image retrieval. The hierarchical sparse codebook includes multiple levels and allows a gradual determination/classification of an image feature of an image into one or more groups or nodes by traversing the image feature through one or more paths to the one or more groups or nodes of the codebook. The image feature is compared with a subset of nodes at each level of the codebook, thereby reducing processing time.

    摘要翻译: 分层稀疏码本允许图像检索中图像的有效搜索和比较。 分级稀疏码本包括多个级别,并且允许通过经由到码本的一个或多个组或节点的一个或多个路径遍历图像特征来将图像的图像特征逐渐确定/分类为一个或多个组或节点。 将图像特征与码本的每个级别的节点子集进行比较,从而减少处理时间。

    Adaptive Image Retrieval Database
    2.
    发明申请
    Adaptive Image Retrieval Database 有权
    自适应图像检索数据库

    公开(公告)号:US20120109943A1

    公开(公告)日:2012-05-03

    申请号:US12938310

    申请日:2010-11-02

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30277 G06F17/30017

    摘要: Adaptive image retrieval image allows retrieval of images that are more likely to reflect a current trend of user preferences and/or interests, and therefore can provide relevant results to an image search. Adaptive image retrieval includes receiving image query log data from one or more clients, and updating a codebook of features based on the received query log data. The image query log data includes images that have been queried by the one or more clients within a predetermined period of time.

    摘要翻译: 自适应图像检索图像允许检索更可能反映用户偏好和/或兴趣的当前趋势的图像,并且因此可以向图像搜索提供相关结果。 自适应图像检索包括从一个或多个客户端接收图像查询日志数据,以及基于接收到的查询日志数据更新特征码本。 图像查询日志数据包括在预定时间段内由一个或多个客户端查询的图像。

    Adaptive image retrieval database
    3.
    发明授权
    Adaptive image retrieval database 有权
    自适应图像检索数据库

    公开(公告)号:US09317533B2

    公开(公告)日:2016-04-19

    申请号:US12938310

    申请日:2010-11-02

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30277 G06F17/30017

    摘要: Adaptive image retrieval image allows retrieval of images that are more likely to reflect a current trend of user preferences and/or interests, and therefore can provide relevant results to an image search. Adaptive image retrieval includes receiving image query log data from one or more clients, and updating a codebook of features based on the received query log data. The image query log data includes images that have been queried by the one or more clients within a predetermined period of time.

    摘要翻译: 自适应图像检索图像允许检索更可能反映用户偏好和/或兴趣的当前趋势的图像,并且因此可以向图像搜索提供相关结果。 自适应图像检索包括从一个或多个客户端接收图像查询日志数据,以及基于接收到的查询日志数据更新特征码本。 图像查询日志数据包括在预定时间段内由一个或多个客户端查询的图像。

    Hierarchical sparse representation for image retrieval
    4.
    发明授权
    Hierarchical sparse representation for image retrieval 有权
    图像检索的分层稀疏表示法

    公开(公告)号:US08463045B2

    公开(公告)日:2013-06-11

    申请号:US12943805

    申请日:2010-11-10

    IPC分类号: G06K9/46 G06K9/36 G06K9/54

    CPC分类号: G06F17/30256

    摘要: A hierarchical sparse codebook allows efficient search and comparison of images in image retrieval. The hierarchical sparse codebook includes multiple levels and allows a gradual determination/classification of an image feature of an image into one or more groups or nodes by traversing the image feature through one or more paths to the one or more groups or nodes of the codebook. The image feature is compared with a subset of nodes at each level of the codebook, thereby reducing processing time.

    摘要翻译: 分层稀疏码本允许图像检索中图像的有效搜索和比较。 分级稀疏码本包括多个级别,并且允许通过经由到码本的一个或多个组或节点的一个或多个路径遍历图像特征来将图像的图像特征逐渐确定/分类为一个或多个组或节点。 将图像特征与码本的每个级别的节点子集进行比较,从而减少处理时间。

    Large scale video event classification
    5.
    发明授权
    Large scale video event classification 有权
    大型视频事件分类

    公开(公告)号:US08842965B1

    公开(公告)日:2014-09-23

    申请号:US13287974

    申请日:2011-11-02

    IPC分类号: H04N5/765

    摘要: Systems and methods are provided herein relating to video classification. A text mining component is disclosed that automatically generates a plurality of video event categories. Part-of-Speech (POS) analysis can be applied to video titles and descriptions, further using a lexical hierarchy to filter potential classifications. Classification performance can be further improved by extracting content-based features from a video sample. Using the content based features a set of classifier scores can be generated. A hyper classifier can use both the classifier scores and the content-based features of the video to classify the video sample.

    摘要翻译: 本文提供了与视频分类相关的系统和方法。 公开了一种自动生成多个视频事件类别的文本挖掘组件。 语音(POS)分析可以应用于视频标题和描述,进一步使用词法层次来过滤潜在的分类。 通过从视频样本中提取基于内容的特征,可以进一步提高分类性能。 使用基于内容的功能可以生成一组分类器分数。 超分类器可以使用分类器分数和视频的基于内容的特征来对视频样本进行分类。