An apparatus includes: display controlling means for displaying, on a display, a viewable-area image representing a viewable area of a captured image having been captured; and accepting means for receiving an instruction to set the viewable-area image as a detectable area in which an object can be detected.

A computer-implemented is disclosed. The method includes: receiving media data of a live media stream; detecting a trigger associated with the media data of the live media stream; in response to detecting the trigger, generating at least one of audio or video overlay content associated with the trigger; and transmitting, to viewer devices, the at least one of audio or video overlay content with the live media stream.

A computer-implemented is disclosed. The method includes: receiving media data of a live media stream; obtaining audience reaction data associated with the live media stream; identifying an event-of-interest in the live media stream based on the audience reaction data, wherein a time of the event-of-interest is prior to a time of the audience reaction data; obtaining a segment of at least one of audio data or video data of the live media stream that is associated with the time of the event-of-interest; generating a digital asset incorporating the segment; and providing the digital asset to at least one viewer of the live media stream.

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, categorizing a temporal position of the identified video frames within the commercial as being in either a beginning or ending portion of the commercial, or a middle portion of the commercial, and assigning to the commercial the identified products or brands as primary metadata candidates when the temporal position of the identified video frames within the commercial is in either the beginning or ending portion of the commercial.

A video processing device includes an acquirer that acquires video data via a predetermined transmission line, the video data including video and metadata that indicates a first frequency band that is a spatial frequency range in which the video is present; an adjuster that makes sharpness gain adjustment to video such that, among a plurality of regions of the video included in the video data acquired by the acquirer, a sharpness gain for a first region that belongs to the first frequency band indicated by the metadata exceeds a sharpness gain for a second region that belongs to a second frequency band that is a range outside the first frequency band; and an output device that outputs video adjusted by the adjuster.

A method for processing video data includes: acquiring a target segment of video data to be extracted; acquiring theme information to be extracted; and determining an association degree between the target segment and the theme information based on segment information of the video data and a relationship between the target segment and the video data.

A method for video quality assessment implemented by a computing device, where the method includes selecting a first set of frames from an input video source, determining features of the first set of frames for input into a first machine learning model, applying the first machine learning model to the features of the first set of frames to obtain a video quality score and a confidence score, and triggering a retraining of the first machine learning model in response to the confidence score being determined to be out of bounds.

The present disclosure provides a video timing labeling method. The method includes: acquiring a video file to be labeled and text information to be inquired; acquiring a video segment matching the text information to be inquired based on a timing labeling network of a timing labeling model; acquiring a video feature of the video segment matching the text information to be inquired based on a feature extraction network of the timing labeling model; acquiring text information corresponding to the video segment labeled in the video file based on a visual text translation network of the timing labeling model; and outputting the video segment matching the text information to be inquired and the text information corresponding to the video segment labeled in the video file based on the timing labeling model.

One or more frames sampled from a first media item of an event are analyzed to identify one or more candidate event periods within the one or more frames. For each of the one or more frames, whether a candidate event period of the one or more candidate event periods satisfies one or more conditions is determined. Responsive to determining that the candidate event period of the one or more candidate event periods satisfies the one or more conditions, the candidate event period is identified as an actual event period used to divide a time the event. Mapping data that maps the actual event period to a timestamp associated with a respective frame of the one or more frames of the first media item is generated.

A method and system for identifying social trends are provided. The method includes collecting multimedia content from a plurality of data sources; gathering environmental variables related to the collected multimedia content; extracting visual elements from the collected multimedia content; generating at least one signature for each extracted visual element; generating at least one cluster of visual elements by clustering at least similar signatures generated for the extracted visual elements; correlating environmental variables related to visual elements in the at least one cluster; determining at least one social trend by associating the correlated environmental variables with the at least one cluster.