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    • 57. 发明授权
    • Image retrieval systems and methods with semantic and feature based relevance feedback
    • 图像检索系统和方法具有基于语义和特征的相关性反馈
    • US07529732B2
    • 2009-05-05
    • US10900574
    • 2004-07-28
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • G06F17/30
    • G06F17/30265G06F17/30256G06F19/00Y10S707/99933Y10S707/99934Y10S707/99935
    • An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.
    • 图像检索系统执行基于关键词和基于内容的图像检索。 用户界面允许用户使用关键字和示例图像的组合来指定查询。 根据输入查询,图像检索系统查找与查询中的关键字匹配的关键字和/或具有类似低级特征(如颜色,纹理和形状)的图像。 系统对图像进行排序并将其返回给用户。 用户界面允许用户识别与查询更相关的图像,以及与查询较少或不相关的图像。 用户可以选择通过从结果集中选择一个示例图像并在新查询中提交其低级特征来优化搜索。 图像检索系统监视用户反馈,并使用它来优化任何搜索工作,并训练自己以用于将来的搜索查询。 在所描述的实现中,图像检索系统将基于特征的相关性反馈和基于语义的相关性反馈无缝集成。
    • 58. 发明申请
    • Function-based Object Model for Use in WebSite Adaptation
    • 基于功能的对象模型用于网站适应
    • US20090100330A1
    • 2009-04-16
    • US12264566
    • 2008-11-04
    • Jin-Lin ChenYudong YangHong-Jiang Zhang
    • Jin-Lin ChenYudong YangHong-Jiang Zhang
    • G06F17/00
    • G06F17/3089
    • By understanding a website author's intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. Various inventive systems and methods analyze a website's function so that its content can be adapted to different client environments, e.g. devices, network conditions, or user preferences. A novel function-based object model automatically identifies objects associated with a website, and analyzes those objects in terms of their functions. The function-based object model permits consistent, informed decisions to be made in the adaptation process, so that web content is displayed not only in an organized manner, but in a manner that reflects the author's intention.
    • 通过对网站功能的分析了解网站作者的意图,网站内容可以以更加欣赏和尊重网站背后的功能的方式进行呈现或呈现。 各种发明的系统和方法分析网站的功能,使得其内容可以适应于不同的客户端环境,例如, 设备,网络条件或用户偏好。 基于功能的新型对象模型自动识别与网站相关联的对象,并根据其功能对这些对象进行分析。 基于功能的对象模型允许在适应过程中做出一致的,明智的决定,使得网页内容不仅以有组织的方式显示,而且以反映作者意图的方式显示。
    • 59. 发明授权
    • Method and system for generating a classifier using inter-sample relationships
    • 使用样本间关系生成分类器的方法和系统
    • US07519217B2
    • 2009-04-14
    • US10997073
    • 2004-11-23
    • Tie-Yan LiuZhike KongHong-Jiang Zhang
    • Tie-Yan LiuZhike KongHong-Jiang Zhang
    • G06K9/62G06K9/68
    • G06K9/00711G06K9/6292
    • A method and system for generating a classifier to classify sub-objects of an object based on a relationship between sub-objects is provided. The classification system provides training sub-objects along with the actual classification of each training sub-object. The classification system may iteratively train sub-classifiers based on feature vectors representing the features of each sub-object, the actual classification of the sub-object, and a weight associated with the sub-object. After a sub-classifier is trained, the classification system classifies the training sub-objects using the trained sub-classifier. The classification system then adjusts the classifications based on relationships between training sub-objects. The classification system assigns a weight for the sub-classifier and weight for each sub-object based on the accuracy of the adjusted classifications.
    • 提供了一种用于生成分类器以根据子对象之间的关系对对象的子对象进行分类的方法和系统。 分类系统提供训练子对象以及每个训练子对象的实际分类。 分类系统可以基于表示每个子对象的特征,子对象的实际分类以及与子对象相关联的权重的特征向量迭代地训练子分类器。 在训练子分类器之后,分类系统使用经过训练的子分类器对训练子对象进行分类。 然后,分类系统基于训练子对象之间的关系来调整分类。 分类系统根据调整后的分类的准确性为每个子对象分配子分类器的权重和权重。
    • 60. 发明授权
    • Robust camera motion analysis for home video
    • 用于家庭视频的强大的相机运动分析
    • US07312819B2
    • 2007-12-25
    • US10720677
    • 2003-11-24
    • Yu-Fei MaHong-Jiang ZhangDongjun Lan
    • Yu-Fei MaHong-Jiang ZhangDongjun Lan
    • H04N5/228G06K9/00
    • G06T7/20H04N5/145H04N17/002
    • A robust camera motion analysis method is described. In an implementation, a method includes analyzing video having sequential frames to determine one or more camera motions that occurred when sequential frames of the video were captured. The one or more camera motions for each frame are described by a set of displacement curves, a mean absolute difference (MAD) curve, and a major motion (MAJ) curve. The set of displacement curves describe the one or more camera motions in respective horizontal (H), vertical (V), and radial (R) directions. The MAD curve relates a minimum MAD value from the set of displacement curves. The MAJ curve is generated from the minimum MAD value and provides one or more qualitative descriptions that describe the one or more camera motions as at least one of still, vertical, horizontal and radial.
    • 描述了鲁棒的摄像机运动分析方法。 在实现中,一种方法包括分析具有顺序帧的视频,以确定在捕获视频的连续帧时发生的一个或多个相机运动。 通过一组位移曲线,平均绝对差(MAD)曲线和主运动(MAJ)曲线来描述每帧的一个或多个相机运动。 位移曲线集描述了水平(H),垂直(V)和径向(R)方向上的一个或多个相机运动。 MAD曲线与位移曲线集合中的最小MAD值相关。 从最小MAD值生成MAJ曲线,并提供描述一个或多个相机运动作为静止,垂直,水平和径向中的至少一个的一个或多个定性描述。