Character-Based Video Summarization

The environment of video production and consumption on social media platforms has undergone a significant change as a result of the widespread usage of the internet and reasonably priced video capture devices. By producing a brief description of each video, video summarizing helps viewers rapidly understand the content of videos. However, standard paging techniques can result in a severe burden on computer systems, while artificial extraction might be time-consuming with a high quantity of missing data. The multi-view description of videos can also be found in the rich textual content that is typically included with videos on social media platforms, such as subtitles or bullet-screen comments. Here, a novel framework for concurrently modelling visual and textual information is proposed in order to achieve that goal. Characters are found randomly using detection techniques, identified by re-identification modules to extract probable key-frames, and then the frames are aggregated as a summary. The subtitles and bullet-screen remarks are also used as multi-source textual information to create a final text summary of the target character from the input video