System, device, and method for generating and utilizing content-aware metadata, particularly for playback of video and other content items. A method includes: receiving a video file, and receiving content-aware metadata about visual objects that are depicted in said video file; and dynamically adjusting or modifying playback of that video file, on a video playback device, based on the content-aware metadata. The modifications include content-aware cropping, summarizing, watermarking, overlaying of other content elements, modifying playback speed, adding user-selectable indicators or areas around or near visual objects to cause a pre-defined action upon user selection, or other adjustments or modification. Optionally, a modified and content-aware version of the video file is automatically generated or stored. Optionally, the content-aware metadata is stored internally or integrally within the video file, in its header or as a private channel; or is stored in an accompanying file.

Methods and systems for detecting and predicting anomalies include processing frames of a video stream to determine values of a feature corresponding to each frame. A feature time series is generated that corresponds to values of the identified feature over time. A matrix profile is generated that identifies similarities of sub-sequences of the time series to other sub-sequences of the feature time series. An anomaly is detected by determining that a value of the matrix profile exceeds a threshold value. An automatic action is performed responsive to the detected anomaly.

Methods and systems for detecting and predicting anomalies include processing frames of a video stream to determine values of a feature corresponding to each frame. A feature time series is generated that corresponds to values of the identified feature over time. A matrix profile is generated that identifies similarities of sub-sequences of the time series to other sub-sequences of the feature time series. An anomaly is detected by determining that a value of the matrix profile exceeds a threshold value. An automatic action is performed responsive to the detected anomaly.

The present disclosure provides a system and method for switching to a real time, dynamic, adaptive and non-sequentially assembled video during streaming of a live video. The method includes fetching an interest profile of a user. The fetching of the interest profile is done based on one or more interactive behaviors of the user. Further, the method includes recommending a set of video recommendations to the user. The method includes assembling one or more logical cluster of mapped fragments of one or more tagged videos virtually to obtain an assembled video. The method includes rendering the assembled video. In addition, the method includes switching the live video to the assembled video dynamically in the real time.

A system and method for navigating digital media assets including a navigation system configured to receive a search query in response to a user input and process the search query by applying the search query to a search index of digital media asset conventional and time-based metadata and determining search results of titles of and start points in time within digital media assets that satisfy the search query. The navigation system may then display the search results to the user through the user interface. The search results may be displayed in a hierarchical format, wherein the title of the digital media asset is displayed and upon selecting the title of the digital media asset, the start points in time within that digital media asset are displayed or played as a video to the user through the user interface.

Methods and systems for calculating, storing, and allowing electronic searches for metadata associated with media titles. The metadata includes scores specific to each actor and each genre of a media title, where the scores indicate the degree to which an actor’s performance in that title corresponds to a particular genre. Electronic searches for particular actors’ performance in a specific genre thus return more accurate results that more correctly reflect how well the actors’ performances reflect that genre.

A media file processing method includes: recognizing content features of a target media file, wherein the content features include an image feature and/or a sound feature; determining a target aggregation theme of the target media file according to the recognized content features of the target media file; determining the target media file as media files under the target aggregation theme; and synthesizing the media files under the target aggregation theme in response to a video clip instruction with respect to the target aggregation theme, to obtain a target video corresponding to the target aggregation theme.

A method for searching a video and equipment with a video search function are provided. The method for searching a video includes constructing a video DB by analyzing continuity of a tag given to an appearing object and extracting section information about the tag, and detecting video information. An object may be recognized, a video database may be constructed, and a video may be searched on the basis of analysis based on an artificial intelligence (AI) model through a 5G network.

Several ways are provided for a viewer of a movie to create a deep tag, that is, a bookmark for a segment of the movie. The deep tag can be associated with descriptive text and sent to an address provided by the viewer, either an e-mail address or an instant messaging address. Additionally, before the deep tag is created, it can be checked whether the content owner of the movie is known. If known, the content owner's rules, if any, regarding deep tagging are followed. If unknown, a set of registered content owners can be alerted of the presence of new content. When ownership of the new content is established, the already-created deep tags can be updated in accordance with the content owner's rules, if any, regarding deep tagging.

Several ways are provided for a viewer of a movie to create a deep tag, that is, a bookmark for a segment of the movie. The deep tag can be associated with descriptive text and sent to an address provided by the viewer, either an e-mail address or an instant messaging address. Additionally, before the deep tag is created, it can be checked whether the content owner of the movie is known. If known, the content owner's rules, if any, regarding deep tagging are followed. If unknown, a set of registered content owners can be alerted of the presence of new content. When ownership of the new content is established, the already-created deep tags can be updated in accordance with the content owner's rules, if any, regarding deep tagging.