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31. 发明授权

US08849030B2 Image retrieval using spatial bag-of-features 有权
标题翻译：使用空间包特征的图像检索
公开(公告)号：US08849030B2
公开(公告)日：2014-09-30
申请号：US13092786
申请日：2011-04-22
申请人： Changhu Wang , Zhiwei Li , Lei Zhang
发明人： Changhu Wang , Zhiwei Li , Lei Zhang
IPC分类号： G06K9/34 , G06K9/46 , G06F17/30
CPC分类号： G06F17/30259 , G06K9/4647 , G06K9/4671
摘要： Local features of retrieved images are identified and for each image, an ordered bag-of-features is created that describes the features of the image. Spatial relationships between features of an image are captured in histogram descriptors created from linear or circular projections. Using the histogram descriptors, ordered bags-of-features describing the features of the images are developed. Calibrating the ordered bags-of-features to account for spatial variance leads to spatial bags-of-features.
摘要翻译：识别检索到的图像的本地特征，并且对于每个图像，创建描述图像的特征的有序的特征袋。图像特征之间的空间关系被捕获在从线性或圆形投影创建的直方图描述符中。使用直方图描述符，开发了描述图像特征的有序的特征袋。校准订购的特征袋以考虑空间差异导致空间特征袋。

32. 发明申请

US20130337675A1 ANTI-LOOSE SOCKET AND PULL-OUT LOCKING MECHANISM THEREOF 有权
标题翻译：防松塞和拉出锁定机构
公开(公告)号：US20130337675A1
公开(公告)日：2013-12-19
申请号：US14002362
申请日：2012-02-28
申请人： Yingfeng Cai , Zhiwei Li
发明人： Yingfeng Cai , Zhiwei Li
IPC分类号： H01R13/639
CPC分类号： H01R13/639 , H01R13/187 , H01R13/20 , H01R13/506 , H01R13/635 , H01R13/6395 , H01R24/76 , H01R2103/00
摘要： The present invention relates to an anti-loose socket and a pull-out locking mechanism thereof, wherein inside the anti-loose socket, there are a pull-out locking mechanism composed of a bevelled sleeve (15) and two cylinders (16) arranged in a symmetrical manner at two sides within the bevelled sleeve; an inside longitudinal section of the bevelled sleeve has a cone angle in an umbrella shape, the middle portion of the bevelled sleeve allows a plug pin (61) to pass through; the cylinder is mounted on a floating block (14) movable up and down, and can move up and down along the inside conical surface of the bevelled sleeve by the floating block. When the plug (6) is pulled out upwards, the cylinder moves upwards due to the action of a friction force and a elastic force, however due to the limiting action of the bevel surface, the cylinders stick to the two bevel surfures more and more tightly, so as to form a self-locking, such that the plug cannot be pulled out or cannot be easily pulled out; when the cylinders drop down, the plug can be conveniently pulled out.
摘要翻译：本发明涉及一种防松销插座及其拉出锁定机构，其特征在于，在防松动插座内设有一个拉出锁定机构，该拉出锁定机构由倾斜套筒（15）和两个气缸（16）构成，在斜切套筒内的两侧以对称的方式; 斜切套筒的内侧纵截面具有伞形的锥角，倾斜套筒的中间部分允许插销（61）通过; 气缸安装在可上下移动的浮动块（14）上，并且可以通过浮动块沿着倾斜套筒的内圆锥形表面上下移动。当插头（6）向上拉出时，由于摩擦力和弹性力的作用，气缸向上移动，然而由于斜面的限制作用，气缸越来越多地粘在两个斜面上紧紧地形成自锁，使得插头不能拉出或不能容易地拉出; 当气瓶下降时，可以方便地拔出插头。

33. 发明授权

US08571850B2 Dual cross-media relevance model for image annotation 有权
标题翻译：用于图像注释的双跨媒体相关性模型
公开(公告)号：US08571850B2
公开(公告)日：2013-10-29
申请号：US11956331
申请日：2007-12-13
申请人： Mingjing Li , Jing Lui , Bin Wang , Zhiwei Li , Wei-Ying Ma
发明人： Mingjing Li , Jing Lui , Bin Wang , Zhiwei Li , Wei-Ying Ma
IPC分类号： G06F17/27
CPC分类号： G06F17/241 , G06F17/2735
摘要： A dual cross-media relevance model (DCMRM) is used for automatic image annotation. In contrast to the traditional relevance models which calculate the joint probability of words and images over a training image database, the DCMRM model estimates the joint probability by calculating the expectation over words in a predefined lexicon. The DCMRM model may be advantageous because a predefined lexicon potentially has better behavior than a training image database. The DCMRM model also takes advantage of content-based techniques and image search techniques to define the word-to-image and word-to-word relations involved in image annotation. Both relations can be estimated by using image search techniques on the web data as well as available training data.
摘要翻译：双重跨媒体相关性模型（DCMRM）用于自动图像注释。与在训练图像数据库中计算单词和图像的联合概率的传统相关性模型相反，DCMRM模型通过计算预定义词典中的单词的期望来估计联合概率。 DCMRM模型可能是有利的，因为预定义词典潜在地具有比训练图像数据库更好的行为。 DCMRM模型还利用基于内容的技术和图像搜索技术来定义图像注释中涉及的单词到图像和单词对字的关系。可以通过使用图像搜索技术对网络数据以及可用的训练数据来估计这两个关系。

34. 发明申请

US20120054177A1 SKETCH-BASED IMAGE SEARCH 有权
标题翻译：基于草图的图像搜索
公开(公告)号：US20120054177A1
公开(公告)日：2012-03-01
申请号：US12873007
申请日：2010-08-31
申请人： Changhu Wang , Zhiwei Li , Lei Zhang
发明人： Changhu Wang , Zhiwei Li , Lei Zhang
IPC分类号： G06F17/30
CPC分类号： G06F17/30259 , G06F17/30277 , G06K9/00402 , G06K9/4604 , G06K9/4609 , G06K9/4671
摘要： Sketch-based image search may include receiving a query curve as a sketch query input and identifying a first plurality of oriented points based on the query curve. The first plurality of oriented points may be used to locate at least one image having a curve that includes a second plurality of oriented points that match at least some of the first plurality of oriented points Implementations also include indexing a plurality of images by identifying at least one curve in each image and generating an index comprising a plurality of oriented points as index entries. The index entries are associated with the plurality of images based on corresponding oriented points in the identified curves in the images.
摘要翻译：基于草图的图像搜索可以包括接收查询曲线作为草图查询输入，并且基于查询曲线来识别第一多个定向点。可以使用第一多个定向点来定位具有曲线的至少一个图像，该曲线包括与第一多个定向点中的至少一些匹配的第二多个定向点。实现还包括通过至少识别多个图像来索引多个图像每个图像中的一个曲线并且生成包括多个定向点作为索引条目的索引。索引条目基于图像中所识别的曲线中的对应的定向点与多个图像相关联。

35. 发明授权

US08126274B2 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：US08126274B2
公开(公告)日：2012-02-28
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。

36. 发明授权

US08081824B2 Generating search requests from multimodal queries 有权
标题翻译：从多模态查询生成搜索请求
公开(公告)号：US08081824B2
公开(公告)日：2011-12-20
申请号：US12247958
申请日：2008-10-08
申请人： Ming Jing Li , Wei-Ying Ma , Xing Xie , Xin Fan , Zhiwei Li
发明人： Ming Jing Li , Wei-Ying Ma , Xing Xie , Xin Fan , Zhiwei Li
IPC分类号： G06K9/46
CPC分类号： G06F17/30864 , Y10S707/99945 , Y10S707/99948
摘要： A method and system for generating a search request from a multimodal query that includes a query image and query text is provided. The multimodal query system identifies images of a collection that are textually related to the query image based on similarity between words associated with each image and the query text. The multimodal query system then selects those images of the identified images that are visually related to the query image. The multimodal query system may formulate a search request based on keywords of web pages that contain the selected images and submit that search request to a search engine service.
摘要翻译：提供了一种用于从包含查询图像和查询文本的多模式查询生成搜索请求的方法和系统。多模式查询系统基于与每个图像相关联的单词与查询文本之间的相似度来识别与查询图像文本相关的集合的图像。多模式查询系统然后选择与查询图像视觉相关的识别图像的那些图像。多模式查询系统可以基于包含所选图像的网页的关键词来制定搜索请求，并将该搜索请求提交给搜索引擎服务。

37. 发明授权

US08027940B2 Classification of images as advertisement images or non-advertisement images 有权
标题翻译：图像分类为广告图像或非广告图像
公开(公告)号：US08027940B2
公开(公告)日：2011-09-27
申请号：US12945635
申请日：2010-11-12
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： G06F15/18
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。

38. 发明申请

US20110194780A1 OBJECT SIMILARITY SEARCH IN HIGH-DIMENSIONAL VECTOR SPACES 有权
标题翻译：对象相似性搜索在高维矢量空间
公开(公告)号：US20110194780A1
公开(公告)日：2011-08-11
申请号：US13092083
申请日：2011-04-21
申请人： Ming Jing Li , Wei-Ying Ma , Zhiwei Li , Bin Wang
发明人： Ming Jing Li , Wei-Ying Ma , Zhiwei Li , Bin Wang
IPC分类号： G06K9/68
CPC分类号： G06F17/3025 , G06F17/30864 , G06K9/4642 , G06K9/6282
摘要： An object search system generates a hierarchical clustering of objects of a collection based on similarity of the objects. The object search system generates a separate hierarchical clustering of objects for multiple features of the objects. To identify objects similar to a target object, the object search system first generates a feature vector for the target object. For each feature of the feature vector, the object search system uses the hierarchical clustering of objects to identify the cluster of objects that is most “feature similar” to that feature of the target object. The object search system indicates the similarity of each candidate object based on the features for which the candidate object is similar.
摘要翻译：对象搜索系统基于对象的相似性生成集合的对象的分层聚类。对象搜索系统为对象的多个特征生成对象的单独分层聚类。为了识别与目标对象类似的对象，对象搜索系统首先生成目标对象的特征向量。对于特征向量的每个特征，对象搜索系统使用对象的分层聚类来识别与目标对象的特征最“特征相似”的对象簇。对象搜索系统基于候选对象相似的特征来指示每个候选对象的相似性。

39. 发明授权

US07877384B2 Scoring relevance of a document based on image text 有权
标题翻译：基于图像文本评估文档的相关性
公开(公告)号：US07877384B2
公开(公告)日：2011-01-25
申请号：US11681161
申请日：2007-03-01
申请人： Qing Yu , Shuming Shi , Zhiwei Li , Ji-Rong Wen , Wei-Ying Ma
发明人： Qing Yu , Shuming Shi , Zhiwei Li , Ji-Rong Wen , Wei-Ying Ma
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06F17/30265
摘要： A method and system for determining relevance of a document having text and images to a text string is provided. A scoring system identifies image text associated with an image of the document. The scoring system calculates an image score indicating relevance of the image text to the text string. The image score may be used in many applications, such as searching, summary generation, and document classification, image search, and image classification.
摘要翻译：提供了一种用于确定具有文本和图像的文档与文本串的相关性的方法和系统。评分系统识别与文档的图像相关联的图像文本。评分系统计算指示图像文本与文本字符串的相关性的图像分数。图像分数可以用于许多应用中，例如搜索，汇总生成和文档分类，图像搜索和图像分类。

40. 发明授权

US07788263B2 Probabilistic retrospective event detection 有权
标题翻译：概率回顾事件检测
公开(公告)号：US07788263B2
公开(公告)日：2010-08-31
申请号：US11256353
申请日：2005-10-21
申请人： Zhiwei Li , Mingjing Li , Wei-Ying Ma
发明人： Zhiwei Li , Mingjing Li , Wei-Ying Ma
IPC分类号： G06F17/30 , G06F17/00
CPC分类号： G06F17/30684 , G06F17/30687
摘要： Probabilistic retrospective event detection is described. In one aspect, event parameters are initialized to identify a number of events from a corpus of documents. Using a generative model, documents are determined to be associated with an event to detect representative events from the identified number of events.
摘要翻译：描述概率回顾事件检测。在一个方面，事件参数被初始化以从文档语料库中识别多个事件。使用生成模型，文档被确定为与事件相关联以从所识别的事件数量检测代表事件。

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