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161 条记录 (耗时 0.037 秒)

    Pose-invariant face recognition system and process
    71.
    发明授权
    Pose-invariant face recognition system and process 有权

    公开(公告)号：US07127087B2

    公开(公告)日：2006-10-24

    申请号：US10983194

    申请日：2004-11-05

    申请人： Fu Jie Huang ,  Hong-Jiang Zhang ,  Tsuhan Chen

    发明人： Fu Jie Huang ,  Hong-Jiang Zhang ,  Tsuhan Chen

    IPC分类号： G06K9/00 ,  G06K9/62

    CPC分类号： G06K9/00228 ,  G06K9/00288 ,  G06K9/6292

    摘要： A face recognition system and process for identifying a person depicted in an input image and their face pose. This system and process entails locating and extracting face regions belonging to known people from a set of model images, and determining the face pose for each of the face regions extracted. All the extracted face regions are preprocessed by normalizing, cropping, categorizing and finally abstracting them. More specifically, the images are normalized and cropped to show only a persons face, categorized according to the face pose of the depicted person's face by assigning them to one of a series of face pose ranges, and abstracted preferably via an eigenface approach. The preprocessed face images are preferably used to train a neural network ensemble having a first stage made up of a bank of face recognition neural networks each of which is dedicated to a particular pose range, and a second stage constituting a single fusing neural network that is used to combine the outputs from each of the first stage neural networks. Once trained, the input of a face region which has been extracted from an input image and preprocessed (i.e., normalized, cropped and abstracted) will cause just one of the output units of the fusing portion of the neural network ensemble to become active. The active output unit indicates either the identify of the person whose face was extracted from the input image and the associated face pose, or that the identity of the person is unknown to the system.

    Image retrieval systems and methods with semantic and feature based relevance feedback
    72.
    发明授权
    Image retrieval systems and methods with semantic and feature based relevance feedback 有权

    公开(公告)号：US07099860B1

    公开(公告)日：2006-08-29

    申请号：US09702292

    申请日：2000-10-30

    申请人： Wen-Yin Liu ,  Hong-Jiang Zhang ,  Ye Lu

    发明人： Wen-Yin Liu ,  Hong-Jiang Zhang ,  Ye Lu

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30265 ,  G06F17/30256 ,  G06F19/00 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935

    摘要： An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.

    Document representation for scalable structure
    74.
    发明申请
    Document representation for scalable structure 有权
    可扩展结构的文档表示

    公开(公告)号：US20050071364A1

    公开(公告)日：2005-03-31

    申请号：US10676518

    申请日：2003-09-30

    申请人： Xing Xie ,  Wei-Ying Ma ,  Hong-Jiang Zhang ,  Liqun Chen

    发明人： Xing Xie ,  Wei-Ying Ma ,  Hong-Jiang Zhang ,  Liqun Chen

    IPC分类号： G06F17/00 ,  G06F17/30

    CPC分类号： G06F17/30905 ,  Y10S707/99942 ,  Y10S707/99943 ,  Y10S707/99944 ,  Y10S707/99945

    摘要： An exemplary system includes a browser to browse a web page based on a web page definition having a slicing tree defining an arrangement of rectangular regions in the web page. The web page definition can include parametric data describing adaptability parameters associated with a rectangular region. A rendering module renders an adapted web page based on the web page definition, and a proxy module generates an intermediary adapted web page definition. A method includes rendering the web page according to a slicing tree and block property data in an associated web page definition. The method may include determining a set of unsummarized blocks that maximize information fidelity.

    摘要翻译： 示例性系统包括浏览器，其基于具有定义网页中的矩形区域布置的切片树的网页定义来浏览网页。 网页定义可以包括描述与矩形区域相关联的适应性参数的参数数据。 呈现模块基于网页定义呈现适应的网页，并且代理模块生成中介适配的网页定义。 一种方法包括根据切片树渲染网页并在相关网页定义中块块属性数据。 该方法可以包括确定使信息保真度最大化的一组未知块。

    Community mining based on core objects and affiliated objects
    75.
    发明申请
    Community mining based on core objects and affiliated objects 失效
    基于核心对象和附属对象的社区挖掘

    公开(公告)号：US20050021531A1

    公开(公告)日：2005-01-27

    申请号：US10624759

    申请日：2003-07-22

    申请人： Ji-Rong Wen ,  Wen-Jun Zhou ,  Wei-Ying Ma ,  Hong-Jiang Zhang

    发明人： Ji-Rong Wen ,  Wen-Jun Zhou ,  Wei-Ying Ma ,  Hong-Jiang Zhang

    IPC分类号： G06F17/30 ,  G06F7/00

    CPC分类号： G06F17/30873 ,  G06F17/30864

    摘要： In community mining based on core objects and affiliated objects, a set of core objects for a community of objects are identified from a plurality of objects. The community is expanded, based on the set of core objects, to include a set of affiliated objects. According to one aspect, a model of a community of objects is obtained by grouping a first collection of a plurality of objects into a center portion, and grouping a second collection of the plurality of objects into one or more concentric portions around the center portion. The groupings of the first and second collections of the objects are identified as the community of objects.

    摘要翻译： 在基于核心对象和附属对象的社区挖掘中，从多个对象中识别出用于对象社区的一组核心对象。 基于一组核心对象扩展社区，包括一组附属对象。 根据一个方面，通过将多个对象的第一集合分组成中心部分并将多个对象的第二集合分组成围绕中心部分的一个或多个同心部分来获得对象社区的模型。 对象的第一和第二集合的分组被标识为对象的社区。

    Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR)
    76.
    发明授权
    Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR) 有权
    相关性最大化，迭代最小化，相关性反馈，基于内容的图像检索（CBIR）

    公开(公告)号：US06748398B2

    公开(公告)日：2004-06-08

    申请号：US09823534

    申请日：2001-03-30

    申请人： Hong-Jiang Zhang ,  Zhong Su ,  Xingquan Zhu

    发明人： Hong-Jiang Zhang ,  Zhong Su ,  Xingquan Zhu

    IPC分类号： G06F1730

    CPC分类号： G06F17/30256 ,  G06K9/6215 ,  G06K9/6253 ,  G06K9/6263 ,  G06K9/6278 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935 ,  Y10S707/99936 ,  Y10S707/99943 ,  Y10S707/99945 ,  Y10S707/99948

    摘要： An implementation of a technology, described herein, for relevance-feedback, content-based facilitating accurate and efficient image retrieval minimizes the number of iterations for user feedback regarding the semantic relevance of exemplary images while maximizing the resulting relevance of each iteration. One technique for accomplishing this is to use a Bayesian classifier to treat positive and negative feedback examples with different strategies. In addition, query refinement techniques are applied to pinpoint the users' intended queries with respect to their feedbacks. These techniques further enhance the accuracy and usability of relevance feedback. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.

    摘要翻译： 这里描述的用于相关性反馈，基于内容的促进精确和有效的图像检索的技术的实现使得关于示例性图像的语义相关性的用户反馈的迭代次数最小化，同时最大化每次迭代的结果相关性。 实现这一点的一种技术是使用贝叶斯分类器来处理具有不同策略的正反馈示例。 另外，使用查询优化技术来针对用户对其反馈的预期查询进行定位。 这些技术进一步提高了相关性反馈的准确性和可用性。 本摘要本身并不旨在限制本专利的范围。 在所附权利要求中指出了本发明的范围。

    Community mining based on core objects and affiliated objects
    77.
    发明授权
    Community mining based on core objects and affiliated objects 失效
    基于核心对象和附属对象的社区挖掘

    公开(公告)号：US07885960B2

    公开(公告)日：2011-02-08

    申请号：US10624759

    申请日：2003-07-22

    申请人： Ji-Rong Wen ,  Wen-Jun Zhou ,  Wei-Ying Ma ,  Hong-Jiang Zhang

    发明人： Ji-Rong Wen ,  Wen-Jun Zhou ,  Wei-Ying Ma ,  Hong-Jiang Zhang

    IPC分类号： G06F17/30 ,  G06F7/00

    CPC分类号： G06F17/30873 ,  G06F17/30864

    摘要： In community mining based on core objects and affiliated objects, a set of core objects for a community of objects are identified from a plurality of objects. The community is expanded, based on the set of core objects, to include a set of affiliated objects. According to one aspect, a model of a community of objects is obtained by grouping a first collection of a plurality of objects into a center portion, and grouping a second collection of the plurality of objects into one or more concentric portions around the center portion. The groupings of the first and second collections of the objects are identified as the community of objects.

    摘要翻译： 在基于核心对象和附属对象的社区挖掘中，从多个对象中识别出用于对象社区的一组核心对象。 基于一组核心对象扩展社区，包括一组附属对象。 根据一个方面，通过将多个对象的第一集合分组成中心部分并将多个对象的第二集合分组成围绕中心部分的一个或多个同心部分来获得对象社区的模型。 对象的第一和第二集合的分组被标识为对象的社区。

    Image retrieval systems and methods with semantic and feature based relevance feedback
    80.
    发明授权
    Image retrieval systems and methods with semantic and feature based relevance feedback 有权
    图像检索系统和方法具有基于语义和特征的相关性反馈

    公开(公告)号：US07529732B2

    公开(公告)日：2009-05-05

    申请号：US10900574

    申请日：2004-07-28

    申请人： Wen-Yin Liu ,  Hong-Jiang Zhang ,  Ye Lu

    发明人： Wen-Yin Liu ,  Hong-Jiang Zhang ,  Ye Lu

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30265 ,  G06F17/30256 ,  G06F19/00 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935

    摘要： An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.

    摘要翻译： 图像检索系统执行基于关键词和基于内容的图像检索。 用户界面允许用户使用关键字和示例图像的组合来指定查询。 根据输入查询，图像检索系统查找与查询中的关键字匹配的关键字和/或具有类似低级特征（如颜色，纹理和形状）的图像。 系统对图像进行排序并将其返回给用户。 用户界面允许用户识别与查询更相关的图像，以及与查询较少或不相关的图像。 用户可以选择通过从结果集中选择一个示例图像并在新查询中提交其低级特征来优化搜索。 图像检索系统监视用户反馈，并使用它来优化任何搜索工作，并训练自己以用于将来的搜索查询。 在所描述的实现中，图像检索系统将基于特征的相关性反馈和基于语义的相关性反馈无缝集成。