Patents by Inventor Pablo Beltran Sanchidrian
Pablo Beltran Sanchidrian has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10817565Abstract: A media content tagging system includes a computing platform having a hardware processor, and a system memory storing a tag selector software code configured to receive media content having segments, each segment including multiple content elements each associated with metadata tags having respective pre-computed confidence scores. For each content element, the tag selector software code assigns each of the metadata tags to at least one tag group, determines a confidence score for each tag group based on the pre-computed confidence scores of its assigned metadata tags, discards tag groups having less than a minimum number of assigned metadata tags, and filters the reduced number of tag groups based on the second confidence score to identify a further reduced number of tag groups. The tag selector software code then selects at least one representative tag group for a segment from among the further reduced number of tag groups.Type: GrantFiled: November 6, 2017Date of Patent: October 27, 2020Assignee: Disney Enterprises, Inc.Inventors: Miquel Angel Farre Guiu, Matthew Petrillo, Monica Alfaro, Pablo Beltran Sanchidrian, Marc Junyent Martin, Evan A. Binder, Anthony M. Accardo, Katharine S. Ettinger, Avner Swerdlow
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Patent number: 10489722Abstract: Systems, methods, and articles of manufacture to perform an operation comprising processing, by a machine learning (ML) algorithm and a ML model, a plurality of images in a first dataset, wherein the ML model was generated based on a plurality of images in a training dataset, receiving user input reviewing a respective set of tags applied to each image in the first data set as a result of the processing, identifying, based on a first confusion matrix generated based on the user input and the sets of tags applied to the images in the first data set, a first labeling error in the training dataset, determining a type of the first labeling error based on a second confusion matrix, and modifying the training dataset based on the determined type of the first labeling error.Type: GrantFiled: July 27, 2017Date of Patent: November 26, 2019Assignee: Disney Enterprises, Inc.Inventors: Miquel Angel Farré Guiu, Marc Junyent Martin, Matthew C. Petrillo, Monica Alfaro Vendrell, Pablo Beltran Sanchidrian, Avner Swerdlow, Katharine S. Ettinger, Evan A. Binder, Anthony M. Accardo
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Patent number: 10469905Abstract: According to one implementation, a content classification system includes a computing platform having a hardware processor and a system memory storing a video asset classification software code. The hardware processor executes the video asset classification software code to receive video clips depicting video assets and each including images and annotation metadata, and to preliminarily classify the images with one or more of the video assets to produce image clusters. The hardware processor further executes the video asset classification software code to identify key features data corresponding respectively to each image cluster, to segregate the image clusters into image super-clusters based on the key feature data, and to uniquely identify each of at least some of the image super-clusters with one of the video assets.Type: GrantFiled: August 3, 2018Date of Patent: November 5, 2019Assignee: Disney Enterprises, Inc.Inventors: Miquel Angel Farre Guiu, Matthew Petrillo, Monica Alfaro Vendrell, Pablo Beltran Sanchidrian, Marc Junyent Martin, Avner Swerdlow, Katharine S. Ettinger, Anthony M. Accardo
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Publication number: 20190138617Abstract: A media content tagging system includes a computing platform having a hardware processor, and a system memory storing a tag selector software code configured to receive media content having segments, each segment including multiple content elements each associated with metadata tags having respective pre-computed confidence scores. For each content element, the tag selector software code assigns each of the metadata tags to at least one tag group, determines a confidence score for each tag group based on the pre-computed confidence scores of its assigned metadata tags, discards tag groups having less than a minimum number of assigned metadata tags, and filters the reduced number of tag groups based on the second confidence score to identify a further reduced number of tag groups. The tag selector software code then selects at least one representative tag group for a segment from among the further reduced number of tag groups.Type: ApplicationFiled: November 6, 2017Publication date: May 9, 2019Inventors: Miquel Angel Farre Guiu, Matthew Petrillo, Monica Alfaro, Pablo Beltran Sanchidrian, Marc Junyent Martin, Evan A. Binder, Anthony M. Accardo, Katharine S. Ettinger, Avner Swerdlow
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Patent number: 10248864Abstract: There is provided a method that includes receiving a video having video shots, and creating video shot groups based on similarities between the video shots, where each video shot group of the video shot groups includes one or more of the video shots and has different ones of the video shots than other video shot groups. The method further includes creating at least one video supergroup including at least one video shot group of the video shot groups based on interactions among the one or more of the video shots in each of the video shot groups, and divide the at least one video supergroup into connected video supergroups, each connected video supergroup of the connected video supergroups including one or more of the video shot groups based on the interactions among the one or more of video shots in each of the video shot groups.Type: GrantFiled: December 3, 2015Date of Patent: April 2, 2019Assignee: Disney Enterprises, Inc.Inventors: Miquel Angel Farre Guiu, Pablo Beltran Sanchidrian, Aljoscha Smolic
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Publication number: 20190034822Abstract: Systems, methods, and articles of manufacture to perform an operation comprising processing, by a machine learning (ML) algorithm and a ML model, a plurality of images in a first dataset, wherein the ML model was generated based on a plurality of images in a training dataset, receiving user input reviewing a respective set of tags applied to each image in the first data set as a result of the processing, identifying, based on a first confusion matrix generated based on the user input and the sets of tags applied to the images in the first data set, a first labeling error in the training dataset, determining a type of the first labeling error based on a second confusion matrix, and modifying the training dataset based on the determined type of the first labeling error.Type: ApplicationFiled: July 27, 2017Publication date: January 31, 2019Inventors: Miquel Angel FARRÉ GUIU, Marc JUNYENT MARTIN, Matthew C. PETRILLO, Monica ALFARO VENDRELL, Pablo Beltran SANCHIDRIAN, Avner SWERDLOW, Katharine S. ETTINGER, Evan A. BINDER, Anthony M. ACCARDO
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Publication number: 20180343496Abstract: According to one implementation, a content classification system includes a computing platform having a hardware processor and a system memory storing a video asset classification software code. The hardware processor executes the video asset classification software code to receive video clips depicting video assets and each including images and annotation metadata, and to preliminarily classify the images with one or more of the video assets to produce image clusters. The hardware processor further executes the video asset classification software code to identify key features data corresponding respectively to each image cluster, to segregate the image clusters into image super-clusters based on the key feature data, and to uniquely identify each of at least some of the image super-clusters with one of the video assets.Type: ApplicationFiled: August 3, 2018Publication date: November 29, 2018Inventors: Miquel Angel Farre Guiu, Matthew Petrillo, Monica Alfaro Vendrell, Pablo Beltran Sanchidrian, Marc Junyent Martin, Avner Swerdlow, Katharine S. Ettinger, Anthony M. Accardo
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Publication number: 20180276286Abstract: There is provided a system including a computing platform having a hardware processor and a memory, and a metadata extraction and management unit stored in the memory. The hardware processor is configured to execute the metadata extraction and management unit to extract a plurality of metadata types from a media asset sequentially and in accordance with a prioritized order of extraction based on metadata type, aggregate the plurality of metadata types to produce an aggregated metadata describing the media asset, use the aggregated metadata to include at least one database entry in a graphical database, wherein the at least one database entry describes the media asset, display a user interface for a user to view tags of metadata associated with the media asset, and correcting presence of one of the tags of metadata associated with the media asset, in response to an input from the user via the user interface.Type: ApplicationFiled: May 21, 2018Publication date: September 27, 2018Inventors: Miquel Angel Farre Guiu, Marc Junyent Martin, Jordi Pont-Tuset, Pablo Beltran Sanchidrian, Nimesh Narayan, Leonid Sigal, Aljoscha Smolic, Anthony M. Accardo
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Patent number: 10057644Abstract: According to one implementation, a content classification system includes a computing platform having a hardware processor and a system memory storing a video asset classification software code. The hardware processor executes the video asset classification software code to receive video clips depicting video assets and each including images and annotation metadata, and to preliminarily classify the images with one or more of the video assets to produce image clusters. The hardware processor further executes the video asset classification software code to identify key features data corresponding respectively to each image cluster, to segregate the image clusters into image super-clusters based on the key feature data, and to uniquely identify each of at least some of the image super-clusters with one of the video assets.Type: GrantFiled: April 26, 2017Date of Patent: August 21, 2018Assignee: Disney Enterprises, Inc.Inventors: Miquel Angel Farre Guiu, Matthew Petrillo, Monica Alfaro Vendrell, Pablo Beltran Sanchidrian, Marc Junyent Martin, Avner Swerdlow, Katharine S. Ettinger, Anthony M. Accardo
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Patent number: 9912974Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a plurality of superclusters that includes at least one of a plurality of shot clusters, wherein each of the shot clusters includes at least one of a plurality of video shots, and wherein each video shot includes one or more video frames, and computing an expected value for a metric based on the plurality of superclusters.Type: GrantFiled: March 1, 2016Date of Patent: March 6, 2018Assignee: Disney Enterprises, Inc.Inventors: Miquel Á. Farré Guiu, Seth Frey, Aljosa Aleksej Andrej Smolic, Michael R. Clements, Pablo Beltran Sanchidrian
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Publication number: 20170257653Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a plurality of superclusters that includes at least one of a plurality of shot clusters, wherein each of the shot clusters includes at least one of a plurality of video shots, and wherein each video shot includes one or more video frames, and computing an expected value for a metric based on the plurality of superclusters.Type: ApplicationFiled: March 1, 2016Publication date: September 7, 2017Inventors: Miquel Á. FARRÉ GUIU, Seth FREY, Aljosa Aleksej Andrej SMOLIC, Michael R. CLEMENTS, Pablo Beltran SANCHIDRIAN
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Publication number: 20170076153Abstract: There is provided a method that includes receiving a video having video shots, and creating video shot groups based on similarities between the video shots, where each video shot group of the video shot groups includes one or more of the video shots and has different ones of the video shots than other video shot groups. The method further includes creating at least one video supergroup including at least one video shot group of the video shot groups based on interactions among the one or more of the video shots in each of the video shot groups, and divide the at least one video supergroup into connected video supergroups, each connected video supergroup of the connected video supergroups including one or more of the video shot groups based on the interactions among the one or more of video shots in each of the video shot groups.Type: ApplicationFiled: December 3, 2015Publication date: March 16, 2017Inventors: Miquel Angel Farre Guiu, Pablo Beltran Sanchidrian, Aljoscha Smolic