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    • 1. 发明申请
    • NEAR-LOSSLESS VIDEO SUMMARIZATION
    • 近无障碍视频总结
    • US20110267544A1
    • 2011-11-03
    • US12768769
    • 2010-04-28
    • Tao MeiXian-Sheng HuaShipeng LiLin-Xie Tang
    • Tao MeiXian-Sheng HuaShipeng LiLin-Xie Tang
    • H04N5/14
    • H04N5/144G06K9/00751G11B27/034G11B27/105G11B27/28H04N19/159H04N19/25H04N19/61H04N21/816H04N21/84H04N21/8453H04N21/8455H04N21/8456H04N21/8549
    • Described is perceptually near-lossless video summarization for use in maintaining video summaries, which operates to substantially reconstruct an original video in a generally perceptually near-lossless manner. A video stream is summarized with little information loss by using a relatively very small piece of summary metadata. The summary metadata comprises an image set of synthesized mosaics and representative keyframes, audio data, and the metadata about video structure and motion. In one implementation, the metadata is computed and maintained (e.g., as a file) to summarize a relatively large video sequence, by segmenting a video shot into subshots, and selecting keyframes and mosaics based upon motion data corresponding to those subshots. The motion data is maintained as a semantic description associated with the image set. To reconstruct the video, the metadata is processed, including simulating motion using the image set and the semantic description, which recovers the audiovisual content without any significant information loss.
    • 描述的是用于维护视频摘要的感知上的近无损视频摘要,其操作以基本上以感知方式近无损的方式基本上重建原始视频。 通过使用相对非常小的汇总元数据,视频流总结了很少的信息丢失。 摘要元数据包括合成马赛克的图像集和代表性的关键帧,音频数据以及关于视频结构和运动的元数据。 在一个实施方式中,通过将视频拍摄分割为子照片,并且基于与这些子图片相对应的运动数据来选择关键帧和马赛克,计算和维护元数据(例如,作为文件)来总结相对较大的视频序列。 运动数据被保持为与图像集相关联的语义描述。 为了重建视频,处理元数据,包括使用图像集和语义描述来模拟运动,其恢复视听内容,而没有任何显着的信息丢失。
    • 3. 发明授权
    • Video concept detection using multi-layer multi-instance learning
    • 使用多层多实例学习的视频概念检测
    • US08804005B2
    • 2014-08-12
    • US12111202
    • 2008-04-29
    • Tao MeiXian-Sheng HuaShipeng LiZhiwei Gu
    • Tao MeiXian-Sheng HuaShipeng LiZhiwei Gu
    • G06K9/62G06K9/34
    • G11B27/28G06K9/00711G06K9/6282
    • Visual concepts contained within a video clip are classified based upon a set of target concepts. The clip is segmented into shots and a multi-layer multi-instance (MLMI) structured metadata representation of each shot is constructed. A set of pre-generated trained models of the target concepts is validated using a set of training shots. An MLMI kernel is recursively generated which models the MLMI structured metadata representation of each shot by comparing prescribed pairs of shots. The MLMI kernel is subsequently utilized to generate a learned objective decision function which learns a classifier for determining if a particular shot (that is not in the set of training shots) contains instances of the target concepts. A regularization framework can also be utilized in conjunction with the MLMI kernel to generate modified learned objective decision functions. The regularization framework introduces explicit constraints which serve to maximize the precision of the classifier.
    • 视频剪辑中包含的视觉概念基于一组目标概念进行分类。 剪辑被分割成镜头,并且构建每个镜头的多层多实例(MLMI)结构化元数据表示。 使用一组训练镜头验证了一组预先生成的目标概念训练模型。 通过比较规定的拍摄对,递归地生成MLMI内核,以对每个镜头的MLMI结构化元数据表示进行建模。 MLMI内核随后被用于生成学习的客观决策函数,该函数学习用于确定特定镜头(不在该组训练镜头中)是否包含目标概念的实例的分类器。 正则化框架也可以与MLMI内核一起使用,以生成修改后的学习目标决策函数。 正则化框架引入明确的约束,用于最大化分类器的精度。
    • 4. 发明授权
    • Enhancing photo browsing through music and advertising
    • 通过音乐和广告加强照片浏览
    • US08504422B2
    • 2013-08-06
    • US12786020
    • 2010-05-24
    • Tao MeiXian-Sheng HuaShipeng LiJinlian GuoFei Sheng
    • Tao MeiXian-Sheng HuaShipeng LiJinlian GuoFei Sheng
    • G06Q30/00
    • G06F17/30056G06F17/30047G06Q30/02G06Q30/0243
    • Techniques for recommending music and advertising to enhance a user's experience while photo browsing are described. In some instances, songs and ads are ranked for relevance to at least one photo from a photo album. The songs, ads and photo(s) from the photo album are then mapped to a style and mood ontology to obtain vector-based representations. The vector-based representations can include real valued terms, each term associated with a human condition defined by the ontology. A re-ranking process generates a relevancy term for each song and each ad indicating relevancy to the photo album. The relevancy terms can be calculated by summing weighted terms from the ranking and the mapping. Recommended music and ads may then be provided to a user, as the user browses a series of photos obtained from the photo album. The ads may be seamlessly embedded into the music in a nonintrusive manner.
    • 描述用于推荐音乐和广告以提高用户在照相浏览时体验的技术。 在某些情况下,歌曲和广告的排名与相册中的至少一张照片相关。 然后将相册中的歌曲,广告和照片映射到风格和心境本体以获得基于矢量的表示。 基于向量的表示可以包括实际值,每个术语与由本体定义的人类条件相关联。 重新排序过程产生每个歌曲的相关术语,每个广告指示相册的相关性。 可以通过从排名和映射求和加权项来计算相关项。 然后,当用户浏览从相册获得的一系列照片时,推荐的音乐和广告可以被提供给用户。 广告可以无缝地嵌入到音乐中。
    • 5. 发明授权
    • Intelligent overlay for video advertising
    • 视频广告的智能覆盖
    • US08369686B2
    • 2013-02-05
    • US12571373
    • 2009-09-30
    • Tao MeiXian-Sheng HuaShipeng LiJinlian Guo
    • Tao MeiXian-Sheng HuaShipeng LiJinlian Guo
    • H04N9/80
    • H04N21/458G06Q30/02G06Q30/0243G11B27/034G11B27/28H04N21/44008H04N21/440236H04N21/466H04N21/812
    • Video advertising overlay technique embodiments are presented that generally detect a set of spatio-temporal nonintrusive positions within a series of consecutive video frames in shots of a digital video and then overlay contextually relevant ads on these positions. In one general embodiment, this is accomplished by decomposing the video into a series of shots, and then identifying a video advertisement for each of a selected set of the shots. The identified video advertisement is one that is determined to be the most relevant to the content of the shot. An overlay area is also identified in each of the shots, where the selected overlay area is the least intrusive among a plurality of prescribed areas to a viewer of the video. The video advertisements identified for the shots are then respectively scheduled to be overlaid in the identified overlay area of a shot, whenever the shot is played.
    • 提供了视频广告覆盖技术实施例,其通常在数字视频的拍摄中检测一系列连续视频帧内的一组时空非侵入位置,然后在这些位置上重叠相关的相关广告。 在一个一般实施例中,这通过将视频分解成一系列镜头,然后为所选择的一组拍摄中的每一个识别视频广告来实现。 所识别的视频广告是被确定为与拍摄内容最相关的广告。 在每个拍摄中还识别覆盖区域,其中所选覆盖区域在多个规定区域中对于视频的观看者是最小的侵入。 每当拍摄被拍摄时,为拍摄而识别的视频广告然后分别被调度为覆盖在所识别的拍摄的重叠区域中。
    • 6. 发明申请
    • Enhancing Photo Browsing through Music and Advertising
    • 通过音乐和广告增强照片浏览
    • US20110288929A1
    • 2011-11-24
    • US12786020
    • 2010-05-24
    • Tao MeiXian-Sheng HuaShipeng LiJinlian GuoFei Sheng
    • Tao MeiXian-Sheng HuaShipeng LiJinlian GuoFei Sheng
    • G06Q30/00G06F17/30G06Q10/00
    • G06F17/30056G06F17/30047G06Q30/02G06Q30/0243
    • Techniques for recommending music and advertising to enhance a user's experience while photo browsing are described. In some instances, songs and ads are ranked for relevance to at least one photo from a photo album. The songs, ads and photo(s) from the photo album are then mapped to a style and mood ontology to obtain vector-based representations. The vector-based representations can include real valued terms, each term associated with a human condition defined by the ontology. A re-ranking process generates a relevancy term for each song and each ad indicating relevancy to the photo album. The relevancy terms can be calculated by summing weighted terms from the ranking and the mapping. Recommended music and ads may then be provided to a user, as the user browses a series of photos obtained from the photo album. The ads may be seamlessly embedded into the music in a nonintrusive manner.
    • 描述用于推荐音乐和广告以提高用户在照相浏览时体验的技术。 在某些情况下,歌曲和广告的排名与相册中的至少一张照片相关。 然后将相册中的歌曲,广告和照片映射到风格和心境本体以获得基于矢量的表示。 基于向量的表示可以包括实际值,每个术语与由本体定义的人类条件相关联。 重新排序过程产生每个歌曲的相关术语,每个广告指示相册的相关性。 可以通过从排名和映射求和加权项来计算相关项。 然后,当用户浏览从相册获得的一系列照片时,推荐的音乐和广告可以被提供给用户。 广告可以无缝地嵌入到音乐中。
    • 9. 发明申请
    • Incentive Selection of Region-of-Interest and Advertisements for Image Advertising
    • 激励选择图像广告领域和广告
    • US20120095825A1
    • 2012-04-19
    • US12906899
    • 2010-10-18
    • Tao MeiXian-Sheng HuaShipeng Li
    • Tao MeiXian-Sheng HuaShipeng Li
    • G06Q30/00
    • G06Q30/0276G06Q30/0244G06Q30/0245
    • Techniques for image selection and region of interest analysis are described herein. A pair of two or more users is configured, and an image is displayed to the pair. The image can be a still image (i.e., a picture) or a moving image (i.e., video). In some instances, a plurality of advertisements is suggested for possible association with the image. Input is received from both users in the pair, indicating a positive or a negative association between each advertisement and the image. When the pair positively rates an advertisement, the advertisement is associated with the image. A plurality of regions of interest within the image may be suggested. In response, positive or negative input is received from the pair indicating whether each of the plurality of regions of interest is appropriately suggested for placement of an advertisement.
    • 本文描述了用于图像选择和感兴趣区域分析的技术。 配置一对两个以上的用户,并且一对图像被显示。 图像可以是静止图像(即,图像)或运动图像(即,视频)。 在一些情况下,建议多个广告以与图像可能的关联。 从该对中的两个用户接收到输入,指示每个广告和图像之间的正或负关联。 当该对对广告进行正比率时,该广告与图像相关联。 可以建议图像内的多个感兴趣区域。 作为响应,从该对接收到正或负输入,指示是否适当地建议多个感兴趣区域中的每一个用于放置广告。