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    Systems and methods for automatically editing a video
    1.
    发明授权
    Systems and methods for automatically editing a video 有权
    自动编辑视频的系统和方法

    公开(公告)号：US07127120B2

    公开(公告)日：2006-10-24

    申请号：US10286348

    申请日：2002-11-01

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

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

    IPC分类号： G06K9/40

    CPC分类号： G11B27/034 ,  G11B27/28

    摘要： Systems and methods to automatically edit a video to generate a video summary are described. In one aspect, sub-shots are extracted from the video. Importance measures are calculated for at least a portion of the extracted sub-shots. Respective relative distributions for sub-shots having relatively higher importance measures as compared to importance measures of other sub-shots are determined. Based on the determined relative distributions, sub-shots that do not exhibit a uniform distribution with respect to other sub-shots in the particular ones are dropped. The remaining sub-shots are connected with respective transitions to generate the video summary.

    摘要翻译： 描述了自动编辑视频以生成视频摘要的系统和方法。 在一方面，从视频中提取子拍摄。 对于提取的子拍摄的至少一部分计算重要性度量。 确定与其他子拍摄重要度量相比具有相对较高重要度量的子投影的相对相对分布。 基于所确定的相对分布，相对于特定的其他子投影，不显示均匀分布的子投影。 剩余的子拍摄与各自的转换相连接以产生视频摘要。

    Learning-based automatic commercial content detection
    2.
    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：US07565016B2

    公开(公告)日：2009-07-21

    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： 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, 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。

    Learning-Based Automatic Commercial Content Detection
    4.
    发明申请
    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：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。

    Learning-based automatic commercial content detection
    5.
    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。

    Systems and methods for personalized karaoke
    7.
    发明申请
    Systems and methods for personalized karaoke 审中-公开
    个性化卡拉OK的系统和方法

    公开(公告)号：US20050123886A1

    公开(公告)日：2005-06-09

    申请号：US10723049

    申请日：2003-11-26

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

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

    IPC分类号： G10H1/36 ,  G10H7/00

    CPC分类号： G10H1/368 ,  G10H1/361 ,  G10H2220/011

    摘要： Systems and methods are described that implement personalized karaoke, wherein a user's personal home video and photographs are used to form a background for the lyrics during a karaoke performance. An exemplary karaoke apparatus is configured to segment visual content to produce a plurality of sub-shots and to segment music to produce a plurality of music sub-clips. Having produced the visual content sub-shots and music sub-clips, the exemplary karaoke apparatus shortens some of the plurality of sub-shots to a length of a corresponding music sub-clip from within the plurality of music sub-clips. The plurality of sub-shots is then displayed as a background to lyrics associated with the music, thereby adding interest to a karaoke performance.

    摘要翻译： 描述了实现个性化卡拉OK的系统和方法，其中用户的个人家庭视频和照片用于在卡拉OK演奏期间形成歌词的背景。 示例性卡拉OK装置被配置为分割可视内容以产生多个子拍摄并分割音乐以产生多个音乐子剪辑。 在产生视觉内容子拍摄和音乐子剪辑之后，示例性卡拉OK装置将多个子拍摄中的一些从多个音乐子剪辑中缩短到相应音乐子剪辑的长度。 然后将多个子拍摄显示为与音乐相关联的歌词的背景，从而增加对卡拉OK演奏的兴趣。

    Tag ranking
    8.
    发明授权
    Tag ranking 有权
    标签排名

    公开(公告)号：US08175847B2

    公开(公告)日：2012-05-08

    申请号：US12415722

    申请日：2009-03-31

    申请人： Hong-Jiang Zhang ,  Dong Liu ,  Meng Wang ,  Linjun Yang ,  Xian-Sheng Hua

    发明人： Hong-Jiang Zhang ,  Dong Liu ,  Meng Wang ,  Linjun Yang ,  Xian-Sheng Hua

    IPC分类号： G06F17/18

    CPC分类号： G06F17/30038

    摘要： Technologies for generating a boosted tag ranking for a media instance, the boosted tag ranking based on probabilistic relevance estimation computed by a probabilistic relevance estimator and tag correlation refining performed by a tag correlation refiner. Such boosted tag rankings may be used for search result ranking, tag recommendation, and group recommendation.

    摘要翻译： 用于生成用于媒体实例的提升的标签排名的技术，基于由概率相关性估计器计算的概率相关性估计的增强的标签排名以及由标签相关性精炼器执行的标签相关性精炼。 这种提升的标签排名可以用于搜索结果排名，标签推荐和组推荐。

    Multi-label active learning
    9.
    发明授权
    Multi-label active learning 有权
    多标签主动学习

    公开(公告)号：US08086549B2

    公开(公告)日：2011-12-27

    申请号：US11958050

    申请日：2007-12-17

    申请人： Guo-Jun Qi ,  Xian-Sheng Hua ,  Yong Rui ,  Hong-Jiang Zhang ,  Shipeng Li

    发明人： Guo-Jun Qi ,  Xian-Sheng Hua ,  Yong Rui ,  Hong-Jiang Zhang ,  Shipeng Li

    IPC分类号： G06F15/18

    CPC分类号： G06N99/005

    摘要： Multi-label active learning may entail training a classifier with a set of training samples having multiple labels per sample. In an example embodiment, a method includes accepting a set of training samples, with the set of training samples having multiple respective samples that are each respectively associated with multiple labels. The set of training samples is analyzed to select a sample-label pair responsive to at least one error parameter. The selected sample-label pair is then submitted to an oracle for labeling.

    摘要翻译： 多标签主动学习可能需要对分类器训练一组具有每个样本的多个标签的训练样本。 在示例实施例中，一种方法包括接受一组训练样本，其中该组训练样本具有多个相应样本，每个样本分别与多个标签相关联。 分析该组训练样本以响应于至少一个误差参数来选择样本标签对。 然后将选定的样品标签对提交给oracle进行标记。

    KERNELIZED SPATIAL-CONTEXTUAL IMAGE CLASSIFICATION
    10.
    发明申请
    KERNELIZED SPATIAL-CONTEXTUAL IMAGE CLASSIFICATION 有权
    识别空间 - 上下文图像分类

    公开(公告)号：US20100074537A1

    公开(公告)日：2010-03-25

    申请号：US12237298

    申请日：2008-09-24

    申请人： Xian-Sheng Hua ,  Guo-Jun Qi ,  Yong Rui ,  Hong-Jiang Zhang

    发明人： Xian-Sheng Hua ,  Guo-Jun Qi ,  Yong Rui ,  Hong-Jiang Zhang

    IPC分类号： G06K9/62

    CPC分类号： G06K9/469 ,  G06K9/6297

    摘要： Kernelized spatial-contextual image classification is disclosed. One embodiment comprises generating a first spatial-contextual model to represent a first image, the first spatial-contextual model having a plurality of interconnected nodes arranged in a first pattern of connections with each node connected to at least one other node, generating a second spatial-contextual model to represent a second image using the first pattern of connections, and estimating the distance between corresponding nodes in the first spatial-contextual model and the second spatial-contextual model based on a relationship with adjacent connected nodes to determine a distance between the first image and the second image.

    摘要翻译： 公开了内核空间上下文图像分类。 一个实施例包括生成第一空间上下文模型以表示第一图像，第一空间上下文模型具有以与连接到至少一个其他节点的每个节点连接的第一连接方式布置的多个互连节点，产生第二空间 - 使用所述第一连接模式来表示第二图像，以及基于与相邻连接节点的关系来估计所述第一空间 - 上下文模型中的对应节点与所述第二空间 - 上下文模型之间的距离，以确定所述第二图像之间的距离 第一个图像和第二个图像。