A method and device for extracting video highlights

Abstract

The present application discloses a method and device for extracting highlights of a video, which acquires the number of bullet chats in each preset time period in the target video, and adaptively Determine the barrage number threshold, avoiding the subjectivity of threshold selection; determine the preset time period in which the barrage number in the target video is greater than the barrage number threshold as a wonderful time period; gather all the wonderful time periods class, to obtain a plurality of clusters, and the start time and end time of each cluster; according to the start time and end time of each cluster, the target video is extracted to obtain the target highlights fragment. The discretization and fragmentation of the highlight time points are avoided by clustering the highlight time segments, which ensures that the target highlight segment has a certain length of time and ensures the excitement of the target highlight segment.

Description

technical field [0001] The present invention relates to the technical field of video clipping, and more specifically, to a method and device for extracting video highlights. Background technique [0002] Watching videos has become an increasingly important part of the entertainment life of Chinese netizens, and online videos have increasingly become the most important way for people to watch videos. There are many online video resources, not only movies, TV, variety shows and other multimedia resources, but also micro movies, selfie videos and other resources. [0003] Videos watched by users are generally recommended by others or selected through popular web video rankings and hits to play. However, there are often some content in the video that is more attractive to users, and there are also some parts that are relatively boring and not of interest to users. For some of these boring parts, users will find that they are not interested after watching them, which not only af...

AI Technical Summary

Problems solved by technology

[0005] However, only finding out the time points when the number of bullet chats exceeds the threshold is prone to the problem of discrete and discontinuous time points. In this way, the time period taken out is very short, and there are few or no fragments with long time spans, and the effect is not good.

The problem with only finding out the period of time when the average number of barrages per second exceeds the threshold is that there may be a lot of barrages at a certain time point in the time interval, and the number of barrages at other time points is very small, so it is also possible that the entire interval The average number of barrages exceeds the threshold, but there is a large time difference between the time point with the most barrages and the time point with the lowest barrages in the entire interval, so the splendor of the continuous intervals taken out will be compromised

Images