An electronic device is provided. The electronic device includes a display, at least one processor, and at least one memory configured to store instructions that cause the at least one processor to obtain first information from a first still image frame that is included in a first moving image, obtain second information from the first moving image, identify at least one image function based on at least one of the first information or the second information, and control the display to display at least one function execution object for executing the at least one image function. Various other embodiments can be provided.

Systems and methods are described for providing a reply to a query related to a media asset. A query may be received from a user while the media asset is being played on a first device, and in response to determining that the query is related to the media asset, a snapshot of the media asset may be captured, where the snapshot comprises a depiction of a first object and a second object, and the snapshot may be generated for display at a second device. In response to determining there is ambiguity whether the query is related to the first or second object, a disambiguating query based on the first and second objects of the snapshot may be generated for simultaneous output with the snapshot. In response to receiving a reply to the disambiguating query, a response to the query may be generated for output based on the reply.

Methods, systems, and techniques for performing a facet search include receiving facet search commencement user input indicating that a search for a facet is to commence; in response to the facet search commencement user input, searching one or more video recordings for the facet; and displaying, on a display, facet image search results depicting the facet, wherein the facet image search results are selected from the one or more video recordings. An artificial neural network may be used for the facet search, and that network may be trained by generating a facet image training set that comprises training images, with the training images depicting a type of facet common to the training images; and training, by using the facet image training set, that neural network to classify the type of facet when a sample image comprising the type of facet is input to that network.

A system and a method for automatic video and/or audio redaction are provided herein. The method may include the following steps: obtaining an input video; obtaining at least one prespecified object, being a visual or an acoustic object or a descriptor thereof; analyzing the input video, to detect a matched object, being an object having descriptors similar to the descriptors of the at least one prespecified object; and generating a redacted video by removing or replacing the matched objects therefrom.

The present invention provides a video file processing method and apparatus, an electronic device, and a computer readable storage medium, relating to the field of video processing. The method comprises: in a preset first editing interface for an original video file, when a trigger instruction for a preset first interaction function is received, displaying a preset second editing interface, the second editing interface comprising a preset interaction label; receiving, in the interaction label, first identification information, which is determined by an editor, of an interaction object to obtain an interaction label comprising the first identification information; and when an editing completion instruction initiated by the editor is received, generating a target video file comprising the interaction label, and publishing the target video file.

Systems, methods and computer readable storage media for collecting and processing progressivistic metadata are described; a structure of files comprising a progressivistic metadata and implementational aspects of various uses thereof are further described.

A clip image to be used as a highlight image, a replay image, or the like in a broadcast or the like is enabled to be generated easily and precisely. For this purpose, an information processing apparatus performs first processing for converting a received image signal into an image signal for real-time processing and transmitting the image signal to an analysis engine that is located outside. Furthermore, the information processing apparatus performs second processing for receiving event extraction information that has been received from the analysis engine and generating setting information of a clip image, by using the event extraction information.

A server receives and rebroadcasts live streaming video content from a video capture device, such as a mobile phone or unmanned surveillance vehicle. The server includes a media server configured to stream selected video content to a client device, a video analysis system configured to analyze the live video content and generate object detection data, a storage system configured to store the generated object detection data and an identifier of the associated live video content, and a search engine configured to receive a text-based search request, search the object detection data stored in the storage system for relevant search results, and generate a list of live and stored video content associated with the relevant search results.

A data storage device and method for object detection and tagging quality of service based on storage workload are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to receive a plurality of image frames for storage in the memory; identify objects in the plurality of image frames; maintain a map that associates each identified object with image frames of the plurality of images frames that contain the identified object; receive a request for image frames that contain an object of interest; and use the map to identify which image frames of the plurality of image frames are associated with the object of interest. Other embodiments are provided.

Automated product identification within hosted and streamed videos is performed based on video content of a video received at an online video platform and text content associated with the video. First embeddings representative of one or more first candidate products are determined based on video content of the video, such as one or more frames selected from within the video. Second embeddings representative of one or more second candidate products are determined based on text content associated with the video, such as a title, description, or transcript of the video. A product candidate index is produced based on the second embeddings. A product identification representative of a product featured in the video is determined based on a comparison of the first embeddings against entries of the product candidate index, such as including by a nearest neighbor search responsive to the comparison. An indication of the product identification is then output at the online video platform.