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    HEAD POSE ASSESSMENT METHODS AND SYSTEMS
    31.
    发明申请
    HEAD POSE ASSESSMENT METHODS AND SYSTEMS 有权
    头部评估方法和系统

    公开(公告)号：US20110050568A1

    公开(公告)日：2011-03-03

    申请号：US12940408

    申请日：2010-11-05

    申请人： Yuxiao HU ,  Lei Zhang ,  Mingjing Li ,  Hong-Jiang Zhang

    发明人： Yuxiao HU ,  Lei Zhang ,  Mingjing Li ,  Hong-Jiang Zhang

    IPC分类号： G06F3/033 ,  G06F3/01

    CPC分类号： G06F3/012 ,  G06K9/00268 ,  G06K9/6211 ,  G06T7/73 ,  G06T2207/30201

    摘要： Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.

    摘要翻译： 提供了改进以有效地评估用户的脸部和头部姿势，使得计算机或类似装置可以跟踪用户对显示装置的注意。 然后可以自动选择用户转向的显示或图形用户界面的区域，而不需要用户提供进一步的输入。 应用前置面部检测器来检测使用者的正面，然后通过部件检测器检测左右眼中心，左/右口角，鼻尖等的关键面部点。 然后，系统通过图像跟踪器跟踪用户的头部，并且通过姿态估计器根据关键面部点和/或置信输出，通过粗略到精细处理确定用户头部的偏航，倾斜和滚动角度和其他姿态信息。

    Generating clusters of images for search results
    32.
    发明授权
    Generating clusters of images for search results 失效
    为搜索结果生成图像群集

    公开(公告)号：US07725451B2

    公开(公告)日：2010-05-25

    申请号：US11337825

    申请日：2006-01-23

    申请人： Feng Jing ,  Lei Zhang ,  Mingjing Li ,  Wei-Ying Ma ,  Chang-Hu Wang

    发明人： Feng Jing ,  Lei Zhang ,  Mingjing Li ,  Wei-Ying Ma ,  Chang-Hu Wang

    IPC分类号： G06F7/00 ,  G06F17/30

    CPC分类号： G06F17/30265

    摘要： A method and system for generating clusters of images for a search result of an image query is provided. When an original image query is received, the search system identifies text associated with the original image query by submitting the original image query to a search engine. The search system identifies phrases from the text of the web page containing the search result. The search system uses each of the identified phrases as an image query and submits the image queries to an image search engine. The search system considers the image search result for each image query to represent a cluster of related images. The search system then presents the clusters of images as the images of the image search result of the original image query.

    摘要翻译： 提供了一种用于生成用于图像查询的搜索结果的图像群集的方法和系统。 当接收到原始图像查询时，搜索系统通过将原始图像查询提交给搜索引擎来识别与原始图像查询相关联的文本。 搜索系统从包含搜索结果的网页的文本中识别短语。 搜索系统使用每个识别的短语作为图像查询，并将图像查询提交给图像搜索引擎。 搜索系统考虑每个图像查询的图像搜索结果来表示相关图像的集群。 然后，搜索系统将图像集合呈现为原始图像查询的图像搜索结果的图像。

    Unified bayesian framework for shape registration
    33.
    发明授权
    Unified bayesian framework for shape registration 失效
    用于形状注册的统一的贝叶斯框架

    公开(公告)号：US07292737B2

    公开(公告)日：2007-11-06

    申请号：US10641608

    申请日：2003-08-15

    申请人： Yi Zhou ,  Lie Gu ,  Lei Zhang ,  Mingjing Li ,  Hong-Jiang Zhang

    发明人： Yi Zhou ,  Lie Gu ,  Lei Zhang ,  Mingjing Li ,  Hong-Jiang Zhang

    IPC分类号： G06K9/32 ,  G06K9/36

    CPC分类号： G06K9/00281 ,  G06K9/621

    摘要： Systems and methods for shape registration are described. In one aspect, training shape vectors are generated from images in an image database. The training shape vectors identify landmark points associated with one or more object types. A distribution of shape in the training shape vectors is represented as a prior of tangent shape in tangent shape space. The prior of tangent shape is then incorporated into a unified Bayesian framework for shape registration.

    摘要翻译： 描述了用于形状配准的系统和方法。 在一个方面，训练形状向量是从图像数据库中的图像生成的。 训练形状向量识别与一个或多个对象类型相关联的地标点。 训练形状矢量中的形状分布被表示为切线形状空间中的切线形状之前。 之前的切线形状然后被并入到用于形状注册的统一的贝叶斯框架中。

    Face annotation for photo management
    35.
    发明授权
    Face annotation for photo management 有权
    面部注释用于照片管理

    公开(公告)号：US07274822B2

    公开(公告)日：2007-09-25

    申请号：US10609974

    申请日：2003-06-30

    申请人： Lei Zhang ,  Longbin Chen ,  Mingjing Li ,  Hong-Jiang Zhang

    发明人： Lei Zhang ,  Longbin Chen ,  Mingjing Li ,  Hong-Jiang Zhang

    IPC分类号： G06K9/62

    CPC分类号： G06F17/30265 ,  G06K9/00288 ,  G06K2009/00328

    摘要： Systems and methods for annotating a face in a digital image are described. In one aspect, a probability model is trained by mapping one or more sets of sample facial features to corresponding names of individuals. A face from an input data set of at least one the digital image is then detected. Facial features are then automatically extracted from the detected face. A similarity measure is them modeled as a posterior probability that the facial features match a particular set of features identified in the probability model. The similarity measure is statistically learned. A name is then inferred as a function of the similarity measure. The face is then annotated with the name.

    摘要翻译： 描述了用于在数字图像中注释面部的系统和方法。 在一个方面，通过将一组或多组样本面部特征映射到个人的相应名称来训练概率模型。 然后检测来自至少一个数字图像的输入数据集的面。 然后从检测到的脸部自动提取面部特征。 相似性度量是他们被模型化为面部特征与在概率模型中识别的特定特征集合相匹配的后验概率。 统计学习相似性度量。 然后将该名称推定为相似性度量的函数。 然后用该名称注明脸部。

    Propagating relevance from labeled documents to unlabeled documents
    36.
    发明申请
    Propagating relevance from labeled documents to unlabeled documents 有权
    从标签文档到未标记的文档传播相关性

    公开(公告)号：US20070203940A1

    公开(公告)日：2007-08-30

    申请号：US11364807

    申请日：2006-02-27

    申请人： Jue Wang ,  Mingjing Li ,  Wei-Ying Ma ,  Zhiwei Li

    发明人： Jue Wang ,  Mingjing Li ,  Wei-Ying Ma ,  Zhiwei Li

    IPC分类号： G06F17/00

    CPC分类号： G06F17/30864

    摘要： A method and system for propagating the relevance of labeled documents to a query to unlabeled documents is provided. The propagation system provides training data that includes queries, documents labeled with their relevance to the queries, and unlabeled documents. The propagation system then calculates the similarity between pairs of documents in the training data. The propagation system then propagates the relevance of the labeled documents to similar, but unlabeled, documents. The propagation system may iteratively propagate labels of the documents until the labels converge on a solution. The training data with the propagated relevances can then be used to train a ranking function.

    摘要翻译： 提供了一种用于将标记的文档的相关性传播到未标记文档的查询的方法和系统。 传播系统提供包括查询，标记为与查询相关的文档以及未标记的文档的培训数据。 传播系统然后计算训练数据中文档对之间的相似度。 传播系统然后将标记的文档的相关性传播到类似但未标记的文档。 传播系统可以迭代地传播文档的标签，直到标签收敛在解决方案上。 然后可以使用具有传播相关性的训练数据来训练排序功能。

    Method and apparatus for distribution-based language model adaptation
    37.
    发明授权
    Method and apparatus for distribution-based language model adaptation 有权
    基于分布式语言模型适应的方法和装置

    公开(公告)号：US07254529B2

    公开(公告)日：2007-08-07

    申请号：US11225543

    申请日：2005-09-13

    申请人： Jianfeng Gao ,  Mingjing Li

    发明人： Jianfeng Gao ,  Mingjing Li

    IPC分类号： G06F17/27 ,  G06F17/28 ,  G10L15/00

    CPC分类号： G06F17/2715 ,  G10L15/065 ,  G10L15/1815

    摘要： A method and apparatus are provided for adapting a language model to a task-specific domain. Under the method and apparatus, the relative frequency of n-grams in a small training set (i.e. task-specific training data set) and the relative frequency of n-grams in a large training set (i.e. out-of-domain training data set) are used to weight a distribution count of n-grams in the large training set. The weighted distributions are then used to form a modified language model by identifying probabilities for n-grams from the weighted distributions.

    摘要翻译： 提供了一种用于使语言模型适应于任务特定领域的方法和装置。 在该方法和装置下，小训练集中的n-gram的相对频率（即任务特定的训练数据集）和大训练集中的n-gram的相对频率（即，域外训练数据集 ）用于在大训练集中加权n-g的分布计数。 然后通过从加权分布中识别n克的概率，将加权分布用于形成修改后的语言模型。

    Media content search engine incorporating text content and user log mining
    38.
    发明授权
    Media content search engine incorporating text content and user log mining 失效
    包含文本内容和用户日志挖掘的媒体内容搜索引擎

    公开(公告)号：US07231381B2

    公开(公告)日：2007-06-12

    申请号：US09805626

    申请日：2001-03-13

    申请人： Mingjing Li ,  Hong-Jiang Zhang ,  Wen-Yin Liu ,  Zhen Chen

    发明人： Mingjing Li ,  Hong-Jiang Zhang ,  Wen-Yin Liu ,  Zhen Chen

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30017 ,  Y10S707/913 ,  Y10S707/915 ,  Y10S707/99933 ,  Y10S707/99935 ,  Y10S707/99936

    摘要： Text features corresponding to pieces of media content (e.g., images, audio, multimedia content, etc.) are extracted from media content sources. One or more text features (e.g., one or more words) for a piece of media content are extracted from text associated with the piece of media content and text feature vectors generated therefrom and used during subsequent searching. Additional low-level feature vectors may also be extracted from the piece of media content and used during the subsequent searching. Relevance feedback can also be received from a user(s) identifying the relevance of pieces of media content rendered to the user in response to his or her search request. The relevance feedback is logged and can be used in determining how to respond to subsequent search requests, such as by modifying feature vectors (e.g., text feature vectors) corresponding to the pieces of media content for which relevance feedback is received.

    摘要翻译： 从媒体内容源提取对应于媒体内容（例如，图像，音频，多媒体内容等）的文本特征。 从与其相关联的文本内容和从其生成的文本特征向量的文本中提取用于一段媒体内容的一个或多个文本特征（例如，一个或多个单词），并在随后的搜索期间使用。 还可以从媒体内容中提取附加的低级特征向量，并在随后的搜索期间使用。 还可以从用户识别响应于他或她的搜索请求而呈现给用户的媒体内容的相关性的用户接收到相关性反馈。 记录相关性反馈，并且可以用于确定如何响应随后的搜索请求，例如通过修改对应于接收到相关性反馈的多条媒体内容的特征向量（例如，文本特征向量）。

    Learning-based automatic commercial content detection
    39.
    发明授权
    Learning-based automatic commercial content detection 失效
    基于学习的自动商业内容检测

    公开(公告)号：US07164798B2

    公开(公告)日：2007-01-16

    申请号：US10368235

    申请日：2003-02-18

    申请人： Xian-Sheng Hua ,  Lie Lu ,  Mingjing Li ,  Hong-Jiang Zhang

    发明人： Xian-Sheng Hua ,  Lie Lu ,  Mingjing Li ,  Hong-Jiang Zhang

    IPC分类号： G06K9/72 ,  H04H9/00

    CPC分类号： G06K9/00711

    摘要： Systems and methods for learning-based automatic commercial content detection are described. In one aspect, program data is divided into multiple segments. The segments are analyzed to determine visual, audio, and context-based feature sets that differentiate commercial content from non-commercial content. The context-based features are a function of single-side left and/or right neighborhoods of segments of the multiple segments.

    摘要翻译： 描述了基于学习的自动商业内容检测的系统和方法。 在一个方面，程序数据被分成多个段。 分析段以确定将商业内容与非商业内容区分开的视觉，音频和基于上下文的特征集。 基于上下文的特征是多个段的单侧左和/或右邻域的函数。