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    • 6. 发明申请
    • AUTOMATIC IMAGE ANNOTATION USING SEMANTIC DISTANCE LEARNING
    • 使用语义距离学习的自动图像注释
    • WO2009152390A2
    • 2009-12-17
    • PCT/US2009/047122
    • 2009-06-11
    • MICROSOFT CORPORATION
    • MEI, TaoHUA, Xian-ShengLI, ShipengWANG, Yong
    • G06F17/00G06F19/00
    • G06F17/3028G06F17/30265
    • Images are automatically annotated using semantic distance learning. Training images are manually annotated and partitioned into semantic clusters. Semantic distance functions (SDFs) are learned for the clusters. The SDF for each cluster is used to compute semantic distance scores between a new image and each image in the cluster. The scores for each cluster are used to generate a ranking list which ranks each image in the cluster according to its semantic distance from the new image. An association probability is estimated for each cluster which specifies the probability of the new image being semantically associated with the cluster. Cluster-specific probabilistic annotations for the new image are generated from the manual annotations for the images in each cluster. The association probabilities and cluster-specific probabilistic annotations for all the clusters are used to generate final annotations for the new image.
    • 图像使用语义远程学习自动注释。 训练图像被手动注释并划分为语义聚类。 为群集学习语义距离函数(SDF)。 每个群集的SDF用于计算新图像和群集中每个图像之间的语义距离分数。 每个群集的分数用于生成排序列表,根据与新图像的语义距离对群集中的每个图像进行排序。 对于指定新图像与集群语义关联的概率的每个集群估计关联概率。 针对新图像的集群特定概率注释是从每个集群中的图像的手动注释生成的。 用于所有集群的关联概率和集群特定概率注释用于生成新图像的最终注释。
    • 7. 发明申请
    • MULTI-MODAL RELEVANCY MATCHING
    • 多模式相关匹配
    • WO2009036392A2
    • 2009-03-19
    • PCT/US2008/076315
    • 2008-09-12
    • MICROSOFT CORPORATION
    • MEI, TaoHUA, Xian-ShengLI, Shipeng
    • G06Q30/00
    • G06Q30/0242G06Q30/02
    • This document describes techniques capable of associating relevant entities, such as advertisements, with insertion points within a media file. These techniques calculate a global relevancy between entities and the media file. These techniques may also calculate a local relevancy between the entities and one or more insertion points within the media file. Both global and local relevancies may employ textual and non-textual information. With use of the calculated global and local relevancies, the techniques associate one or more entities with each of the one or more insertion points in the media file. These techniques thus enable, for each insertion point, associating a most relevant entity for a particular insertion point with the insertion point. Therefore, when a user consumes the media file the user may also consume a most relevant entity at and for each insertion point in the media file.
    • 该文件描述了能够将相关实体(例如广告)与媒体文件内的插入点相关联的技术。 这些技术计算实体和媒体文件之间的全局相关性。 这些技术还可以计算媒体文件内的实体与一个或多个插入点之间的本地相关性。 全球和当地的相关性都可以使用文本和非文本信息。 利用计算出的全局和局部相关性,这些技术将一个或多个实体与媒体文件中的一个或多个插入点中的每一个相关联。 因此,这些技术使得对于每个插入点,将用于特定插入点的最相关实体与插入点相关联。 因此,当用户使用媒体文件时,用户也可以在媒体文件中的每个插入点消耗最相关的实体。
    • 9. 发明申请
    • ENRICHING ONLINE VIDEOS BY CONTENT DETECTION, SEARCHING, AND INFORMATION AGGREGATION
    • 通过内容检测,搜索和信息聚合增强在线视频
    • WO2011139448A2
    • 2011-11-10
    • PCT/US2011/031046
    • 2011-04-04
    • MICROSOFT CORPORATION
    • MEI, TaoHUA, Xian-ShengLI, Shipeng
    • G06Q50/00H04N21/236
    • G06K9/00751G06F17/30017G06F17/30828G06K9/00765G06Q30/02H04N21/4622H04N21/4722
    • Many internet users consume content through online videos. For example, users may view movies, television shows, music videos, and/or homemade videos. It may be advantageous to provide additional information to users consuming the online videos. Unfortunately, many current techniques may be unable to provide additional information relevant to the online videos from outside sources. Accordingly, one or more systems and/or techniques for determining a set of additional information relevant to an online video are disclosed herein. In particular, visual, textual, audio, and/or other features may be extracted from an online video (e.g., original content of the online video and/or embedded advertisements). Using the extracted features, additional information (e.g., images, advertisements, etc.) may be determined based upon matching the extracted features with content of a database. The additional information may be presented to a user consuming the online video.
    • 许多互联网用户通过在线视频消费内容。 例如,用户可以观看电影,电视节目,音乐视频和/或自制视频。 向消费在线视频的用户提供附加信息可能是有利的。 不幸的是,许多当前的技术可能无法提供与来自外部来源的在线视频相关的附加信息。 因此,本文公开了用于确定与在线视频相关的一组附加信息的一个或多个系统和/或技术。 特别地,可以从在线视频(例如,在线视频和/或嵌入式广告的原始内容)提取视觉,文本,音频和/或其他特征。 使用所提取的特征,可以基于将所提取的特征与数据库的内容相匹配来确定附加信息(例如,图像,广告等)。 附加信息可以被呈现给使用在线视频的用户。