Microsoft Technology Licensing, LLC

Avner Levi

Oron Nir

Irit Ofer

Haim Sabo

Ika Bar-Menachem

Ohad Jassin

Eylon Ami

Lei Zhang

Ori Ziv

Tucker Cunningham Burns

Ella Ben Tov

Apar Singhal

Maria Zontak

Royi Ronen

Yonit Hoffman

Olivier Nano

Mor Geva Pipek

Reut Amior

Anika Zaman

Chin-Yew Lin

Maayan Yedidia

Daniel Nurieli

Systems and methods for spatial-textual clustering-based recognition of text in videos are disclosed. A method includes performing textual clustering on a first subset of a set of predictions that correspond to numeric characters only and performing spatial-textual clustering on a second subset of the set of predictions that correspond to alphabetical characters only. The method includes, for each cluster of predictions associated with the first subset of the set of predictions, choosing a first cluster representative to correct any errors in each cluster of predictions associated with the first subset of the set of predictions and outputting any recognized numeric characters. The method includes, for each cluster of predictions associated with the second subset of the set of predictions, choosing a second cluster representative to correct any errors in each cluster of predictions associated with the second subset of the set of predictions and outputting any recognized alphabetical characters.

Clustering-based recognition of text in videos

A system for indexing animated content receives detections extracted from a media file, where each one of the detections includes an image extracted from a corresponding frame of the media file that corresponds to a detected instance of an animated character. The system determines, for each of the received detections, an embedding defining a set of characteristics for the detected instance. The embedding associated with each detection is provided to a grouping engine that is configured to dynamically configure at least one grouping parameter based on a total number of the detections received. The grouping engine is also configured to sort the detections into groups using the grouping parameter and the embedding for each detection. A character ID is assigned to each one of the groups of detections, and the system indexes the groups of detections in a database in association with the character ID assigned to each group.

Dynamic detection and recognition of media subjects

The technology described herein is directed to systems, methods, and software for indexing video. In an implementation, a method comprises identifying one or more regions of interest around target content in a frame of the video. Further, the method includes identifying, in a portion of the frame outside a region of interest, potentially empty regions adjacent to the region of interest. The method continues with identifying at least one empty region of the potentially empty regions that satisfies one or more criteria and classifying at least the one empty region as a negative sample of the target content. In some implementations, the negative sample of the target content in a set of negative samples of the target content, with which to train a machine learning model employed to identify instances of the target content.

Negative sampling algorithm for enhanced image classification

The technology described herein is directed to a media indexer framework including a character recognition engine that automatically detects and groups instances (or occurrences) of characters in a multi-frame animated media file. More specifically, the character recognition engine automatically detects and groups the instances (or occurrences) of the characters in the multi-frame animated media file such that each group contains images associated with a single character. The character groups are then labeled and used to train an image classification model. Once trained, the image classification model can be applied to subsequent multi-frame animated media files to automatically classifying the animated characters included therein.

Semi supervised target recognition in video

In various embodiments, methods and systems for implementing a media management system, for video data processing and adaptation data generation, are provided. At a high level, a video data processing engine relies on different types of video data properties and additional auxiliary data resources to perform video optical character recognition operations for recognizing characters in video data. In operation, video data is accessed to identify recognized characters. A video OCR operation to perform on the video data for character recognition is determined from video character processing and video auxiliary data processing. Video auxiliary data processing includes processing an auxiliary reference object; the auxiliary reference object is an indirect reference object that is a derived input element used as a factor in determining the recognized characters. The video data is processed based on the video OCR operation and based on processing the video data, at least one recognized character is communicated.

Media management system for video data processing and adaptation data generation

Semi supervised animated character recognition in video

Systems and methods are disclosed for inferring topics from a file containing both audio and video, for example a multimodal or multimedia file, in order to facilitate video indexing. A set of entities is extracted from the file and linked to produce a graph, and reference information is also obtained for the set of entities. Entities may be drawn, for example, from Wikipedia categories, or other large ontological data sources. Analysis of the graph, using unsupervised learning, permits determining clusters in the graph. Extracting features from the clusters, possibly using supervised learning, provides for selection of topic identifiers. The topic identifiers are then used for indexing the file.

Inferring topics with entity linking and ontological data

In various embodiments, methods and systems for implementing video segmentation are provided. A video management system implements a video segment manager that supports generating enhanced segmented video. Enhanced segmented video is a time-based segment of video content. Enhanced segmented video is generated based on a video content cognitive index, segmentation dimensions, segmentation rules and segment reconstruction rules. The video content cognitive index is built for indexing video content. Segmentation rules are applied to the video content to break the video content into time-based segments, the time-based segments are associated with corresponding segmentation dimensions for the video content. Segment reconstruction rules are then applied to the time-based segments to reconstruct the time-based segments into enhanced segmented video. The enhanced segmented video and corresponding values of the segmentation dimensions can be leveraged as distinct portions of the video content for different types of functionality in the video management system.

Video segmentation and searching by segmentation dimensions

In various embodiments, methods and systems for implementing video segment playlist generated are provided. A video management system implements a video segment manager that supports generating video segment playlists for video content. Generating a video segment playlist is based on enhanced segmented video associated with segmentation dimensions. An enhanced segmented video is a time-based segment of video content generated based on segmentation dimensions, segmentation rules and segment reconstruction rules. The video segment manager receives a search query. The video segment manager identifies a plurality of relevant enhanced segmented videos that satisfy the search query. A selection of at least a subset of the plurality of relevant enhanced segmented videos is received to generate a video segment playlist. The video segment manager generates the video segment playlist comprising references to the subset of the plurality of relevant enhanced segmented videos. The video segment playlist comprising the references is communicated and can be used for video playback.

Video management system for generating video segment playlist using enhanced segmented videos

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Kiryat Ono, Israel

Avner Levi