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公开(公告)号：US20150332124A1
公开(公告)日：2015-11-19
申请号：US14810181
申请日：2015-07-27
Applicant: Microsoft Technology Licensing, LLC
Inventor： Linjun Yang , Lifeng Shang , Xian-Sheng Hua , Fei Wang
CPC classification number: G06K9/6215 , G06F16/783 , G06K9/00751 , G06K9/00758 , G06K9/4609 , G06K9/4652
Abstract: A similarity of a first video to a second video may be identified automatically. Images are received from the videos, and divided into sub-images. The sub-images are evaluated based on a feature common to each of the sub-images. Binary representations of the images may be created based on the evaluation of the sub-images. A similarity of the first video to the second video may be determined based on a number of occurrences of a binary representation in the first video and the second video.
Abstract translation: 可以自动识别第一视频与第二视频的相似度。 从视频接收图像，并分成子图像。 基于每个子图像共有的特征来评估子图像。 可以基于子图像的评估来创建图像的二进制表示。 可以基于第一视频和第二视频中的二进制表示的出现次数来确定第一视频与第二视频的相似度。
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公开(公告)号：US09785866B2
公开(公告)日：2017-10-10
申请号：US14602524
申请日：2015-01-22
Applicant: Microsoft Technology Licensing, LLC.
Inventor： Xian-Sheng Hua , Jin Li , Ishan Misra
CPC classification number: G06K9/66 , G06K9/6218 , G06K9/6269 , G06K9/6284 , G06N99/005
Abstract: Techniques for optimizing multi-class image classification by leveraging negative multimedia data items to train and update classifiers are described. The techniques describe accessing positive multimedia data items of a plurality of multimedia data items, extracting features from the positive multimedia data items, and training classifiers based at least in part on the features. The classifiers may include a plurality of model vectors each corresponding to one of the individual labels. The system may iteratively test the classifiers using positive multimedia data and negative multimedia data and may update one or more model vectors associated with the classifiers differently, depending on whether multimedia data items are positive or negative. Techniques for applying the classifiers to determine whether a new multimedia data item is associated with a topic based at least in part on comparing similarity values with corresponding statistics derived from classifier training are also described.
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公开(公告)号：US20160358036A1
公开(公告)日：2016-12-08
申请号：US15240838
申请日：2016-08-18
Applicant: Microsoft Technology Licensing, LLC
Inventor： Linjun Yang , Xian-Sheng Hua , Yang Cai
Abstract: Techniques describe submitting a video clip as a query by a user. A process retrieves images and information associated with the images in response to the query. The process decomposes the video clip into a sequence of frames to extract the features in a frame and to quantize the extracted features into descriptive words. The process further tracks the extracted features as points in the frame, a first set of points to correspond to a second set of points in consecutive frames to construct a sequence of points. Then the process identifies the points that satisfy criteria of being stable points and being centrally located in the frame to represent the video clip as a bag of descriptive words for searching for images and information related to the video clip.
Abstract translation: 技术描述提交视频剪辑作为用户的查询。 响应于查询，进程检索与图像相关联的图像和信息。 该过程将视频剪辑分解成帧序列以提取帧中的特征并将提取的特征量化为描述性词。 该过程进一步跟踪提取的特征作为帧中的点，第一组点对应于连续帧中的第二组点以构成点序列。 然后，该过程识别满足稳定点的标准并且位于帧中心的点以将视频剪辑表示为用于搜索与视频剪辑相关的图像和信息的描述词的一袋。
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公开(公告)号：US10521692B2
公开(公告)日：2019-12-31
申请号：US14324375
申请日：2014-07-07
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jingdong Wang , Xian-Sheng Hua
Abstract: Techniques for intelligent image search results summarization and browsing scheme are described. Images having visual attributes are evaluated for similarities based in part on their visual attributes. At least one preference score indicating a probability of an image to be selected into a summary is calculated for each image. Images are selected based on the similarity of the selected images to the other images and the preference scores of the selected images. A summary of the plurality of images is generated including the selected one individual image.
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5.发明申请ENRICHING ONLINE VIDEOS BY CONTENT DETECTION, SEARCHING, AND INFORMATION AGGREGATION 审中-公开通过内容检测，搜索和信息聚合增强在线视频公开(公告)号：US20160358025A1
公开(公告)日：2016-12-08
申请号：US15241891
申请日：2016-08-19
Applicant: Microsoft Technology Licensing, LLC
Inventor： Tao Mei , Xian-Sheng Hua , Shipeng Li
CPC classification number: G06K9/00751 , G06F16/40 , G06F16/735 , G06K9/00765 , G06Q30/02 , H04N21/4622 , H04N21/4722
Abstract: 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.
Abstract translation: 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。
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Patent Agency Ranking
公开(公告)号：US10592769B2
公开(公告)日：2020-03-17
申请号：US15240838
申请日：2016-08-18
Applicant: Microsoft Technology Licensing, LLC
Inventor： Linjun Yang , Xian-Sheng Hua , Yang Cai
Abstract: Techniques describe submitting a video clip as a query by a user. A process retrieves images and information associated with the images in response to the query. The process decomposes the video clip into a sequence of frames to extract the features in a frame and to quantize the extracted features into descriptive words. The process further tracks the extracted features as points in the frame, a first set of points to correspond to a second set of points in consecutive frames to construct a sequence of points. Then the process identifies the points that satisfy criteria of being stable points and being centrally located in the frame to represent the video clip as a bag of descriptive words for searching for images and information related to the video clip.
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公开(公告)号：US10013637B2
公开(公告)日：2018-07-03
申请号：US14602494
申请日：2015-01-22
Applicant: Microsoft Technology Licensing, LLC.
Inventor： Ishan Misra , Jin Li , Xian-Sheng Hua
IPC: G06K9/62
CPC classification number: G06K9/6227 , G06K9/6218 , G06K9/623 , G06K9/6262
Abstract: Optimizing multi-class image classification by leveraging patch-based features extracted from weakly supervised images to train classifiers is described. A corpus of images associated with a set of labels may be received. One or more patches may be extracted from individual images in the corpus. Patch-based features may be extracted from the one or more patches and patch representations may be extracted from individual patches of the one or more patches. The patches may be arranged into clusters based at least in part on the patch-based features. At least some of the individual patches may be removed from individual clusters based at least in part on determined similarity values that are representative of similarity between the individual patches. The system may train classifiers based in part on patch-based features extracted from patches in the refined clusters. The classifiers may be used to accurately and efficiently classify new images.
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公开(公告)号：US09875301B2
公开(公告)日：2018-01-23
申请号：US14266228
申请日：2014-04-30
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Xian-Sheng Hua , Jin Li , Yoshitaka Ushiku
CPC classification number: G06F17/30705 , G06F17/30675 , G06F17/30864 , G06N99/005
Abstract: Systems and methods for learning topic models from unstructured data and applying the learned topic models to recognize semantics for new data items are described herein. In at least one embodiment, a corpus of multimedia data items associated with a set of labels may be processed to generate a refined corpus of multimedia data items associated with the set of labels. Such processing may include arranging the multimedia data items in clusters based on similarities of extracted multimedia features and generating intra-cluster and inter-cluster features. The intra-cluster and the inter-cluster features may be used for removing multimedia data items from the corpus to generate the refined corpus. The refined corpus may be used for training topic models for identifying labels. The resulting models may be stored and subsequently used for identifying semantics of a multimedia data item input by a user.
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公开(公告)号：US09788080B2
公开(公告)日：2017-10-10
申请号：US15383256
申请日：2016-12-19
Applicant: Microsoft Technology Licensing, LLC
Inventor： Xian-Sheng Hua , Wei Lai , Wei-Ying Ma , Shipeng Li
IPC: H04N7/10 , H04N21/81 , H04N21/2387 , H04N21/234 , H04N7/173
CPC classification number: H04N21/812 , H04N7/17318 , H04N21/23424 , H04N21/2387 , H04N21/47202 , H04N21/6587 , H04N21/8133
Abstract: Systems and methods for automatically inserting advertisements into source video content playback streams are described. In one aspect, the systems and methods communicate a source video content playback stream to a video player to present source video to a user. During playback of the source video, and in response to receipt of a request from the user to navigate portions of the source video (e.g., a user command to fast forward the source video, rewind the source video, or other action), the systems and methods dynamically define a video advertisement clip insertion point (e.g., and insertion point based on a current playback position). The systems and methods then insert a contextually relevant and/or targeted video advertisement clip into the playback stream for presentation to the user.
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公开(公告)号：US09646227B2
公开(公告)日：2017-05-09
申请号：US14445463
申请日：2014-07-29
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Nitin Suri , Xian-Sheng Hua , Tzong-Jhy Wang , William D. Sproule , Andrew S. Ivory , Jin Li
CPC classification number: G06K9/6256 , G06K9/00744 , G06T7/20 , G06T2207/10016
Abstract: This disclosure describes techniques for training models from video data and applying the learned models to identify desirable video data. Video data may be labeled to indicate a semantic category and/or a score indicative of desirability. The video data may be processed to extract low and high level features. A classifier and a scoring model may be trained based on the extracted features. The classifier may estimate a probability that the video data belongs to at least one of the categories in a set of semantic categories. The scoring model may determine a desirability score for the video data. New video data may be processed to extract low and high level features, and feature values may be determined based on the extracted features. The learned classifier and scoring model may be applied to the feature values to determine a desirability score associated with the new video data.
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