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61. 发明申请

US20120139832A1 Head Pose Assessment Methods And Systems 有权
标题翻译：头姿评估方法与系统
公开(公告)号：US20120139832A1
公开(公告)日：2012-06-07
申请号：US13398171
申请日：2012-02-16
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： G06F3/01
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。

62. 发明申请

US20110264659A1 TRAINING A RANKING FUNCTION USING PROPAGATED DOCUMENT RELEVANCE 审中-公开
标题翻译：使用传播文件相关性来训练排序功能
公开(公告)号：US20110264659A1
公开(公告)日：2011-10-27
申请号：US13175804
申请日：2011-07-01
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： G06F17/30
CPC分类号： G06F16/951 , G06F16/3331
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。

63. 发明申请

US20090060351A1 Visual Language Modeling for Image Classification 有权
标题翻译：图像分类的视觉语言建模
公开(公告)号：US20090060351A1
公开(公告)日：2009-03-05
申请号：US11847959
申请日：2007-08-30
申请人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Lei Wu
发明人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Lei Wu
IPC分类号： G06K9/62
CPC分类号： G06K9/4685 , G06K9/4642 , G06K9/6278
摘要： Systems and methods for visual language modeling for image classification are described. In one aspect the systems and methods model training images corresponding to multiple image categories as matrices of visual words. Visual language models are generated from the matrices. In view of a given image, for example, provided by a user or from the Web, the systems and methods determine an image category corresponding to the given image. This image categorization is accomplished by maximizing the posterior probability of visual words associated with the given image over the visual language models. The image category, or a result corresponding to the image category, is presented to the user.
摘要翻译：描述了用于图像分类的视觉语言建模的系统和方法。在一个方面，系统和方法将对应于多个图像类别的训练图像建模为视觉词的矩阵。视觉语言模型是从矩阵生成的。考虑到例如由用户或从Web提供的给定图像，系统和方法确定对应于给定图像的图像类别。这种图像分类是通过在视觉语言模型上最大化与给定图像相关联的视觉词的后验概率来实现的。图像类别或与图像类别对应的结果被呈现给用户。

64. 发明申请

US20080313031A1 CLASSIFICATION OF IMAGES AS ADVERTISEMENT IMAGES OR NON-ADVERTISEMENT IMAGES 有权
标题翻译：图像分类作为广告图像或非广告图像
公开(公告)号：US20080313031A1
公开(公告)日：2008-12-18
申请号：US11762553
申请日：2007-06-13
申请人： Mingjing Li , Zhiwei Li , Dongfang Li , Bin Wang
发明人： Mingjing Li , Zhiwei Li , Dongfang Li , Bin Wang
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0277
摘要： An advertisement image classification system trains a binary classifier to classify images as advertisement images or non-advertisement images and then uses the binary classifier to classify images of web pages as advertisement images or non-advertisement images. During a training phase, the classification system generates training data of feature vectors representing the images and labels indicating whether an image is an advertisement image or a non-advertisement image. The classification system trains a binary classifier to classify images using training data. During a classification phase, the classification system inputs a web page with an image and generates a feature vector for the image. The classification system then applies the trained binary classifier to the feature vector to generate a score indicating whether the image is an advertisement image or a non-advertisement image.
摘要翻译：广告图像分类系统训练二进制分类器将图像分类为广告图像或非广告图像，然后使用二进制分类器将网页的图像分类为广告图像或非广告图像。在训练阶段，分类系统生成表示图像的特征向量的训练数据，以及指示图像是广告图像还是非广告图像的标签。分类系统训练二进制分类器，以使用训练数据对图像进行分类。在分类阶段，分类系统输入具有图像的网页，并生成图像的特征向量。然后，分类系统将经过训练的二进制分类器应用于特征向量，以生成指示图像是广告图像还是非广告图像的分数。

65. 发明申请

US20080152201A1 Efficient Propagation for Face Annotation 审中-公开
标题翻译：面部注释的有效传播
公开(公告)号：US20080152201A1
公开(公告)日：2008-06-26
申请号：US12047247
申请日：2008-03-12
申请人： Lei Zhang , Mingjing Li , Wei-Ying Ma , Yan-Feng Sun , Yuxiao Hu
发明人： Lei Zhang , Mingjing Li , Wei-Ying Ma , Yan-Feng Sun , Yuxiao Hu
IPC分类号： G06K9/46 , G06K9/00
CPC分类号： G06K9/00288 , G06F16/54 , G06F16/58 , G06K9/6221 , G06K2009/00328 , Y10S707/99945 , Y10S707/99948
摘要： Systems, engines, user interfaces, and methods allow a user to select a group of images, such as digital photographs, and assign to the group of images the name of a person who is represented in each of the images. The name is automatically propagated to the face of the person, each time the person's face occurs in an image. In one implementation, names and associations are shared between a browsing mode for viewing multiple images at once and a viewer mode, for viewing one image at a time. The browsing mode can provide a menu of candidate names for annotating a face in a single image of the viewer mode. Likewise, the viewer mode can provide annotated face information to the browser mode for facilitating name propagation. Identification of a person's face in multiple images can be accomplished not only by finding similarities in facial features but also by finding similarities in contextual features near the face in different images.
摘要翻译：系统，引擎，用户界面和方法允许用户选择一组图像，例如数字照片，并且在图像组中分配在每个图像中表示的人的姓名。每当人的脸发生在图像中时，名称将自动传播到人的脸部。在一个实现中，名称和关联在用于一次查看多个图像的浏览模式和观看者模式之间共享，以便一次查看一个图像。浏览模式可以提供用于在观看者模式的单个图像中注释脸部的候选名称的菜单。类似地，观看者模式可以向浏览器模式提供注释的面部信息，以便于名称传播。可以通过在面部特征中发现相似性，而且通过在不同图像中的脸部附近的上下文特征中找到相似性来实现多个图像中的人脸识别。

66. 发明授权

US07391888B2 Head pose assessment methods and systems 有权
标题翻译：头姿势评估方法和系统
公开(公告)号：US07391888B2
公开(公告)日：2008-06-24
申请号：US10452783
申请日：2003-05-30
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： G06K9/00
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。

67. 发明授权

US07336890B2 Automatic detection and segmentation of music videos in an audio/video stream 有权
标题翻译：在音频/视频流中自动检测和分割音乐视频
公开(公告)号：US07336890B2
公开(公告)日：2008-02-26
申请号：US10370314
申请日：2003-02-19
申请人： Lie Lu , Yan-Feng Sun , Mingjing Li , Xian-Sheng Hua , Hong-Jiang Zhang
发明人： Lie Lu , Yan-Feng Sun , Mingjing Li , Xian-Sheng Hua , Hong-Jiang Zhang
IPC分类号： H04N7/00 , H04N5/91 , H04N5/93 , G06K9/46 , G10L11/00 , G06F15/173
CPC分类号： H04H60/37 , G06F17/30787 , G06F17/30796 , G06K9/00711 , G11B27/034 , G11B27/28 , G11B2220/218 , G11B2220/2545 , G11B2220/2562 , H04H60/58 , H04H60/59 , H04H60/74 , H04N5/147 , H04N5/4401 , H04N5/602 , H04N21/4332 , H04N21/4394 , H04N21/44008 , H04N21/44204 , H04N21/8456
摘要： A “music video parser” automatically detects and segments music videos in a combined audio-video media stream. Automatic detection and segmentation is achieved by integrating shot boundary detection, video text detection and audio analysis to automatically detect temporal boundaries of each music video in the media stream. In one embodiment, song identification information, such as, for example, a song name, artist name, album name, etc., is automatically extracted from the media stream using video optical character recognition (OCR). This information is then used in alternate embodiments for cataloging, indexing and selecting particular music videos, and in maintaining statistics such as the times particular music videos were played, and the number of times each music video was played.
摘要翻译： “音乐视频解析器”自动检测并分割组合的音频 - 视频媒体流中的音乐视频。通过集成镜头边界检测，视频文本检测和音频分析来自动检测和分割，可以自动检测媒体流中每个音乐视频的时间边界。在一个实施例中，使用视频光学字符识别（OCR）从媒体流中自动提取歌曲识别信息，例如歌曲名称，歌手姓名，专辑名称等。然后，将该信息用于编目，索引和选择特定音乐视频以及维持诸如特定音乐视频播放的时间的统计数据以及播放每个音乐视频的次数的备选实施例。

68. 发明授权

US07257273B2 Hierarchical scheme for blur detection in digital image using wavelet transform 有权
标题翻译：使用小波变换的数字图像中模糊检测的分层方案
公开(公告)号：US07257273B2
公开(公告)日：2007-08-14
申请号：US10646387
申请日：2003-08-22
申请人： Mingjing Li , Hao Wu , Hong-Jiang Zhang
发明人： Mingjing Li , Hao Wu , Hong-Jiang Zhang
IPC分类号： G06K9/36 , G06K9/46
CPC分类号： G06T7/12 , G06T2207/10016 , G06T2207/20016 , G06T2207/20064
摘要： Methods and apparatuses are provided for detecting blur within digital images using wavelet transform and/or Cepstrum analysis blur detection techniques that are able to detect motion blur and/or out-of-focus blur.
摘要翻译：提供了用于使用能够检测运动模糊和/或离焦模糊的小波变换和/或倒谱分析模糊检测技术来检测数字图像内的模糊的方法和装置。

69. 发明授权

US07233708B2 Systems and methods for indexing and retrieving images 失效
标题翻译：索引和检索图像的系统和方法
公开(公告)号：US07233708B2
公开(公告)日：2007-06-19
申请号：US10703300
申请日：2003-11-07
申请人： Mingjing Li , Lei Zhang , Yan-Feng Sun , Hong-Jiang Zhang
发明人： Mingjing Li , Lei Zhang , Yan-Feng Sun , Hong-Jiang Zhang
IPC分类号： G06K9/54
CPC分类号： G06F17/30262 , G06T7/33 , G06T7/37 , G06T7/42 , G06T2207/20056
摘要： Systems and methods for indexing and retrieving images are described herein. The systems and methods analyze an image to determine its texture moments. The pixels of the image are converted to gray scale. Textural attributes of the pixels are determined. The textural attributes are associated with the local texture of the pixels and are derived from coefficients of Discrete Fourier Transform associated with the pixels. Statistical values associated with the textural attributes of the pixels are calculated. The texture moments of the image are determined from the statistical value.
摘要翻译：本文描述了用于索引和检索图像的系统和方法。系统和方法分析图像以确定其纹理矩。图像的像素被转换成灰度级。确定像素的纹理属性。纹理属性与像素的局部纹理相关联，并且从与像素相关联的离散傅立叶变换的系数导出。计算与像素的纹理属性相关联的统计值。根据统计值确定图像的纹理矩。

70. 发明申请

US20070112583A1 Learning-Based Automatic Commercial Content Detection 失效
标题翻译：基于学习的自动商业内容检测
公开(公告)号：US20070112583A1
公开(公告)日：2007-05-17
申请号：US11623304
申请日：2007-01-15
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： G06Q10/00
CPC分类号： G06K9/00711
摘要： Systems and methods for learning-based automatic commercial content detection are described. In one aspect, the systems and methods include a training component and an analyzing component. The training component trains a commercial content classification model using a kernel support vector machine. The analyzing component analyzes program data such as video and audio data using the commercial content classification model and one or more of single-side left neighborhood(s) and right neighborhood(s) of program data segments. Based on this analysis, each of the program data segments are classified as being commercial or non-commercial 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。一方面，系统和方法包括训练组件和分析组件。训练组件使用内核支持向量机训练商业内容分类模型。分析组件使用商业内容分类模型和程序数据段的单侧左邻居和右邻居中的一个或多个来分析诸如视频和音频数据的程序数据。基于此分析，每个程序数据段被分类为商业或非商业领域。

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