Small form factor web browsing
    71.
    发明授权
    Small form factor web browsing 有权
    小尺寸网页浏览

    公开(公告)号:US09483577B2

    公开(公告)日:2016-11-01

    申请号:US13230513

    申请日:2011-09-12

    IPC分类号: G06F17/00 G06F17/30

    CPC分类号: G06F17/30905

    摘要: A large web page is analyzed and partitioned into smaller sub-pages so that a user can navigate the web page on a small form factor device. The user can browse the sub-pages to find and read information in the content of the large web page. The partitioning can be performed at a web server, an edge server, at the small form factor device, or can be distributed across one or more such devices. The analysis leverages design habits of a web page author to extract a representation structure of an authored web page. The extracted representation structure includes high level structure using several markup language tag selection rules and low level structure using visual boundary detection in which visual units of the low level structure are provided by clustering markup language tags. User viewing habits can be learned to display favorite parts of a web page.

    摘要翻译: 分析大型网页并将其划分为更小的子页面,以便用户可以在小尺寸设备上浏览网页。 用户可以浏览子页面,以便在大型网页的内容中查找和读取信息。 分区可以在Web服务器,边缘服务器,小尺寸设备处执行,或者可以分布在一个或多个这样的设备上。 分析利用网页作者的设计习惯来提取创作网页的表示结构。 所提取的表示结构包括使用几种标记语言标签选择规则的高级结构和使用视觉边界检测的低级结构,其中通过聚类标记语言标签提供低级结构的视觉单元。 可以学习用户观看习惯来显示网页的喜爱部分。

    Function-based object model for use in WebSite adaptation
    72.
    发明授权
    Function-based object model for use in WebSite adaptation 有权
    基于功能的对象模型用于WebSite适配

    公开(公告)号:US08122345B2

    公开(公告)日:2012-02-21

    申请号:US12264566

    申请日:2008-11-04

    IPC分类号: G06F17/00

    CPC分类号: G06F17/3089

    摘要: By understanding a website author's intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. Various inventive systems and methods analyze a website's function so that its content can be adapted to different client environments, e.g. devices, network conditions, or user preferences. A novel function-based object model automatically identifies objects associated with a website, and analyzes those objects in terms of their functions. The function-based object model permits consistent, informed decisions to be made in the adaptation process, so that web content is displayed not only in an organized manner, but in a manner that reflects the author's intention.

    摘要翻译: 通过对网站功能的分析了解网站作者的意图,网站内容可以以更加欣赏和尊重网站背后的功能的方式进行呈现或呈现。 各种发明的系统和方法分析网站的功能,使得其内容可以适应于不同的客户端环境,例如, 设备,网络条件或用户偏好。 基于功能的新型对象模型自动识别与网站相关联的对象,并根据其功能对这些对象进行分析。 基于功能的对象模型允许在适应过程中做出一致的,明智的决定,使得网页内容不仅以有组织的方式显示,而且以反映作者意图的方式显示。

    Small Form Factor Web Browsing
    74.
    发明申请
    Small Form Factor Web Browsing 有权
    小尺寸网页浏览

    公开(公告)号:US20120005565A1

    公开(公告)日:2012-01-05

    申请号:US13230513

    申请日:2011-09-12

    IPC分类号: G06F17/00

    CPC分类号: G06F17/30905

    摘要: A large web page is analyzed and partitioned into smaller sub-pages so that a user can navigate the web page on a small form factor device. The user can browse the sub-pages to find and read information in the content of the large web page. The partitioning can be performed at a web server, an edge server, at the small form factor device, or can be distributed across one or more such devices. The analysis leverages design habits of a web page author to extract a representation structure of an authored web page. The extracted representation structure includes high level structure using several markup language tag selection rules and low level structure using visual boundary detection in which visual units of the low level structure are provided by clustering markup language tags. User viewing habits can be learned to display favorite parts of a web page.

    摘要翻译: 分析大型网页并将其划分为更小的子页面,以便用户可以在小尺寸设备上浏览网页。 用户可以浏览子页面,以便在大型网页的内容中查找和读取信息。 分区可以在Web服务器,边缘服务器,小尺寸设备处执行,或者可以分布在一个或多个这样的设备上。 分析利用网页作者的设计习惯来提取创作网页的表示结构。 所提取的表示结构包括使用几种标记语言标签选择规则的高级结构和使用视觉边界检测的低级结构,其中通过聚类标记语言标签提供低级结构的视觉单元。 可以学习用户观看习惯来显示网页的喜爱部分。

    Method and system for constructing a 3D representation of a face from a 2D representation
    76.
    发明授权
    Method and system for constructing a 3D representation of a face from a 2D representation 有权
    用于从2D表示构造面部的3D表示的方法和系统

    公开(公告)号:US07646909B2

    公开(公告)日:2010-01-12

    申请号:US12194467

    申请日:2008-08-19

    IPC分类号: G06K9/00

    CPC分类号: G06K9/00288 G06K9/00208

    摘要: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.

    摘要翻译: 提供了一种用于从2D图像生成面部的3D图像的方法和系统,用于在3D图像的不同图像条件下生成面部的2D图像,并且基于所生成的2D图像来识别目标面部的2D图像。 识别系统提供了一种面部的3D模型,其包括在标准图像条件下的标准面的3D图像和指示单个脸部与标准脸部的变化的参数。 为了生成面部的3D图像,识别系统在标准图像条件下输入面部的2D图像。 识别系统然后计算将2D图像的点映射到标准面的2D图像的对应点的参数。 识别系统使用这些参数与3D模型在不同图像条件下生成脸部的3D图像。

    Method and system for learning-based quality assessment of images
    77.
    发明授权
    Method and system for learning-based quality assessment of images 有权
    图像学习质量评估方法与系统

    公开(公告)号:US07545985B2

    公开(公告)日:2009-06-09

    申请号:US11029913

    申请日:2005-01-04

    IPC分类号: G06K9/62

    CPC分类号: G06T7/0002 G06K9/036

    摘要: A method and system for learning-based assessment of the quality of an image is provided. An image quality assessment system trains an image classifier based on a training set of sample images that have quality ratings. To train the classifier, the assessment system generates a feature vector for each sample image representing various attributes of the image. The assessment system may train the classifier using an adaptive boosting technique to calculate a quality score for an image. Once the classifier is trained, the assessment system may calculate the quality of an image by generating a feature vector for that image and applying the trained classifier to the feature vector to calculate the quality score for the image.

    摘要翻译: 提供了一种用于基于学习的图像质量评估方法和系统。 图像质量评估系统基于具有质量等级的样本图像的训练集来训练图像分类器。 为了训练分类器,评估系统为表示图像的各种属性的每个样本图像生成特征向量。 评估系统可以使用自适应增强技术训练分类器来计算图像的质量分数。 一旦分类器被训练,评估系统可以通过生成该图像的特征向量来计算图像的质量,并将经训练的分类器应用于特征向量以计算图像的质量得分。