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1. 发明授权

US08232996B2 Image learning, automatic annotation, retrieval method, and device 有权
标题翻译：图像学习，自动注释，检索方法和设备
公开(公告)号：US08232996B2
公开(公告)日：2012-07-31
申请号：US12468423
申请日：2009-05-19
申请人： Timothee Bailloeul , Caizhi Zhu , Yinghul Xu
发明人： Timothee Bailloeul , Caizhi Zhu , Yinghul Xu
IPC分类号： G06T11/20 , G06F15/16
CPC分类号： G06F17/30256 , G06F17/30265 , G06K9/6247
摘要： A first image having annotations is segmented into one or more image regions. Image feature vectors and text feature vectors are extracted from all the image regions to obtain an image feature matrix and a text feature matrix. The image feature matrix and the text feature matrix are projected into a sub-space to obtain the projected image feature matrix and the text feature matrix. The projected image feature matrix and the text feature matrix are stored. First links between the image regions, second links between the first image and the image regions, third links between the first image and the annotations, and fourth links between the annotations are established. Weights of all the links are calculated. A graph showing a triangular relationship between the first image, image regions, and annotations is obtained based on all the links and the weights of the links.
摘要翻译：具有注释的第一图像被分割成一个或多个图像区域。从所有图像区域提取图像特征向量和文本特征向量以获得图像特征矩阵和文本特征矩阵。将图像特征矩阵和文本特征矩阵投影到子空间中以获得投影图像特征矩阵和文本特征矩阵。存储投影图像特征矩阵和文本特征矩阵。建立图像区域之间的第一链接，第一图像和图像区域之间的第二链接，第一图像和注释之间的第三链接以及注释之间的第四链接。计算所有链接的重量。基于链接的所有链接和权重，获得显示第一图像，图像区域和注释之间的三角形关系的图形。

2. 发明申请

US20120063282A1 Systems and Methods for Improved Control of Spindle Speed During Optical Media Seek Operations 审中-公开
标题翻译：在光学媒体寻求操作中改进主轴转速控制的系统和方法
公开(公告)号：US20120063282A1
公开(公告)日：2012-03-15
申请号：US12521462
申请日：2009-06-01
申请人： Cong Cao , CaiZhi Zhu , BoWen Chen
发明人： Cong Cao , CaiZhi Zhu , BoWen Chen
IPC分类号： G11B19/26
CPC分类号： G11B19/28
摘要： Improved control of spindle speed during optical media seek operations is provided by adjusting the spindle motor speed during the actual optical pickup unit movement. In response to receiving a seek instruction to move an optical pickup unit to a target position, the current signal frequency corresponding to a current spindle motor speed may be determined. A target signal frequency corresponding to a desired spindle motor speed at the target position may also be computed. Thereafter, the current spindle motor speed may be adjusted towards the desired spindle motor speed prior to the optical pickup unit reaching the target position.
摘要翻译：通过在实际光学拾取单元移动期间调节主轴电机速度来提供光学介质寻道操作期间对主轴转速的改进控制。响应于接收到将光学拾取单元移动到目标位置的寻道指令，可以确定与当前主轴电机速度相对应的当前信号频率。也可以计算与目标位置的期望的主轴电机速度对应的目标信号频率。此后，可以在光学拾取单元达到目标位置之前，将目前的主轴电机速度调整到期望的主轴电机速度。

3. 发明申请

US20110225172A1 SYSTEM, METHOD, AND COMPUTER-READABLE MEDIUM FOR SEEKING REPRESENTATIVE IMAGES IN IMAGE SET 有权
标题翻译：用于查找图像集中的代表图像的系统，方法和计算机可读介质
公开(公告)号：US20110225172A1
公开(公告)日：2011-09-15
申请号：US13033016
申请日：2011-02-23
申请人： Yuan LIU , Gang Wang , Tao Li , Yinghui Xu , Caizhi Zhu
发明人： Yuan LIU , Gang Wang , Tao Li , Yinghui Xu , Caizhi Zhu
IPC分类号： G06F17/30
CPC分类号： G06F17/30265
摘要： Disclosed are a system, a method, and a computer-readable medium for seeking representative images in an image set. The method comprises a text feature extracting step of extracting text features of each of the plural images; a diversity data obtaining step of obtaining diversity data of the image set based on the text features; a representative score calculating method of calculating a representative score of each of the plural images based on the diversity data; and a representative image selecting step of selecting one or more of the images in the image set based on the representative score of the corresponding images.
摘要翻译：公开了一种用于在图像集中寻找代表性图像的系统，方法和计算机可读介质。该方法包括提取多个图像中的每一个的文本特征的文本特征提取步骤; 分集数据获取步骤，基于所述文本特征获得所述图像集合的分集数据; 基于分集数据计算多个图像中的每一个的代表分数的代表分数计算方法; 以及代表图像选择步骤，基于相应图像的代表性分数来选择图像集中的一个或多个图像。

4. 发明授权

US08204889B2 System, method, and computer-readable medium for seeking representative images in image set 有权
标题翻译：用于在图像集中寻找代表性图像的系统，方法和计算机可读介质
公开(公告)号：US08204889B2
公开(公告)日：2012-06-19
申请号：US13033016
申请日：2011-02-23
申请人： Yuan Liu , Gang Wang , Tao Li , Yinghui Xu , Caizhi Zhu
发明人： Yuan Liu , Gang Wang , Tao Li , Yinghui Xu , Caizhi Zhu
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30265
摘要： System, method, and computer-readable medium for seeking representative images in an image set. Text features of each of the plural images are extracted. Diversity data of the image set is obtained based on the text features. A representative score of each of the plural images is calculated based on the diversity data. One or more of the images in the image set is selected as a representative image based on the representative score of the corresponding images.
摘要翻译：用于在图像集中寻找代表性图像的系统，方法和计算机可读介质。提取多个图像中的每一个的文本特征。基于文本特征获得图像集合的分集数据。基于分集数据计算多个图像中的每一个的代表分数。基于相应图像的代表性分数，选择图像集中的一个或多个图像作为代表图像。

5. 发明申请

US20090289942A1 IMAGE LEARNING, AUTOMATIC ANNOTATION, RETRIEVAL METHOD, AND DEVICE 有权
标题翻译：图像学习，自动评估，检索方法和设备
公开(公告)号：US20090289942A1
公开(公告)日：2009-11-26
申请号：US12468423
申请日：2009-05-19
申请人： Timothee Bailloeul , Caizhi Zhu , Yinghui Xu
发明人： Timothee Bailloeul , Caizhi Zhu , Yinghui Xu
IPC分类号： G06T11/20 , G06K9/46 , G06K9/36
CPC分类号： G06F17/30256 , G06F17/30265 , G06K9/6247
摘要： A first image having annotations is segmented into one or more image regions. Image feature vectors and text feature vectors are extracted from all the image regions to obtain an image feature matrix and a text feature matrix. The image feature matrix and the text feature matrix are projected into a sub-space to obtain the projected image feature matrix and the text feature matrix. The projected image feature matrix and the text feature matrix are stored. First links between the image regions, second links between the first image and the image regions, third links between the first image and the annotations, and fourth links between the annotations are established. Weights of all the links are calculated. A graph showing a triangular relationship between the first image, image regions, and annotations is obtained based on all the links and the weights of the links.
摘要翻译：具有注释的第一图像被分割成一个或多个图像区域。从所有图像区域提取图像特征向量和文本特征向量以获得图像特征矩阵和文本特征矩阵。将图像特征矩阵和文本特征矩阵投影到子空间中以获得投影图像特征矩阵和文本特征矩阵。存储投影图像特征矩阵和文本特征矩阵。建立图像区域之间的第一链接，第一图像和图像区域之间的第二链接，第一图像和注释之间的第三链接以及注释之间的第四链接。计算所有链接的重量。基于链接的所有链接和权重，获得显示第一图像，图像区域和注释之间的三角形关系的图形。

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