Dual Cross-Media Relevance Model for Image Annotation
    51.
    发明申请
    Dual Cross-Media Relevance Model for Image Annotation 有权
    图像注释的双重跨媒体相关性模型

    公开(公告)号:US20090076800A1

    公开(公告)日:2009-03-19

    申请号:US11956331

    申请日:2007-12-13

    IPC分类号: G06F17/21

    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。

    Bipartite Graph Reinforcement Modeling to Annotate Web Images
    52.
    发明申请
    Bipartite Graph Reinforcement Modeling to Annotate Web Images 有权
    用于注释Web图像的二分图加固建模

    公开(公告)号:US20090063455A1

    公开(公告)日:2009-03-05

    申请号:US11848157

    申请日:2007-08-30

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30265 G06F17/30864

    摘要: Systems and methods for bipartite graph reinforcement modeling to annotate web images are described. In one aspect the systems and methods implement bipartite graph reinforcement modeling operations to identify a set of annotations that are relevant to a Web image. The systems and methods annotate the Web image with the identified annotations. The systems and methods then index the annotated Web image. Responsive to receiving an image search query from a user, wherein the image search query comprises information relevant to at least a subset of the identified annotations, the image search engine service presents the annotated Web image to the user.

    摘要翻译: 描述了用于注释网络图像的二分图加强建模的系统和方法。 在一个方面,系统和方法实现二分图加强建模操作,以识别与Web图像相关的一组注释。 系统和方法用已识别的注释注释Web图像。 系统和方法然后索引注释的Web图像。 响应于从用户接收图像搜索查询,其中所述图像搜索查询包括与所识别的注释的至少一个子集相关的信息,所述图像搜索引擎服务将所述注释的Web图像呈现给所述用户。

    Detecting Duplicate Images Using Hash Code Grouping
    54.
    发明申请
    Detecting Duplicate Images Using Hash Code Grouping 有权
    使用哈希代码分组检测重复的图像

    公开(公告)号:US20070239756A1

    公开(公告)日:2007-10-11

    申请号:US11277727

    申请日:2006-03-28

    IPC分类号: G06F7/00

    CPC分类号: G06F17/30864

    摘要: A duplicate image detection system generates an image table that maps hash codes of images to their corresponding images. The image table may group images according to their group identifiers generated from the most significant elements of the hash codes based on significance of the elements in representing an image. The image table thus segregates images by their group identifiers. To detect a duplicate image of a target image, the detection system generates a target hash code for the target image. The detection system then identifies the group of the target image based on the group identifier of the target hash code. After identifying the group identifier, the detection system searches the corresponding group table to identify hash codes that have values that are similar to the target hash code. The detection system then selects the images associated with those similar hash codes as being duplicates of the target image.

    摘要翻译: 复制图像检测系统生成将图像的哈希码映射到其对应图像的图像表。 图像表可以根据基于代表图像的元素的重要性从哈希码的最重要元素生成的组标识符来对图像进行分组。 因此,图像表通过其组标识符隔离图像。 为了检测目标图像的重复图像,检测系统生成目标图像的目标散列码。 然后,检测系统基于目标散列码的组标识符来识别目标图像的组。 在识别组标识符之后,检测系统搜索对应的组表以识别具有与目标散列码相似的值的散列码。 然后,检测系统选择与这些类似的哈希码相关联的图像作为目标图像的重复。

    Generating clusters of images for search results
    55.
    发明申请
    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:US20070174269A1

    公开(公告)日:2007-07-26

    申请号:US11337825

    申请日:2006-01-23

    IPC分类号: 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。

    Speedup of face detection in digital images
    56.
    发明授权
    Speedup of face detection in digital images 有权
    加快数字图像中的人脸检测

    公开(公告)号:US07190829B2

    公开(公告)日:2007-03-13

    申请号:US10610245

    申请日:2003-06-30

    IPC分类号: G06K9/00

    CPC分类号: G06K9/6256 G06K9/00234

    摘要: Improved methods and apparatuses are provided for use in face detection. The methods and apparatuses significantly reduce the number of candidate windows within a digital image that need to be processed using more complex and/or time consuming face detection algorithms. The improved methods and apparatuses include a skin color filter and an adaptive non-face skipping scheme.

    摘要翻译: 提供改进的方法和装置用于面部检测。 这些方法和装置显着地减少了使用更复杂和/或耗时的面部检测算法需要处理的数字图像内的候选窗口数量。 改进的方法和装置包括皮肤滤色器和自适应非面部跳过方案。

    Head pose assessment methods and systems
    57.
    发明授权
    Head pose assessment methods and systems 有权
    头姿势评估方法和系统

    公开(公告)号:US08457358B2

    公开(公告)日:2013-06-04

    申请号:US13398171

    申请日:2012-02-16

    IPC分类号: G06K9/00

    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。

    Head Pose Assessment Methods And Systems
    58.
    发明申请
    Head Pose Assessment Methods And Systems 有权
    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

    IPC分类号: G06F3/01

    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。

    TRAINING A RANKING FUNCTION USING PROPAGATED DOCUMENT RELEVANCE
    59.
    发明申请
    TRAINING A RANKING FUNCTION USING PROPAGATED DOCUMENT RELEVANCE 审中-公开
    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

    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。

    Visual Language Modeling for Image Classification
    60.
    发明申请
    Visual Language Modeling for Image Classification 有权
    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

    IPC分类号: G06K9/62

    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。