Football video highlight automatic synthesis method based on event model

Abstract

The invention relates to a football video highlight automatic synthesis method based on an event model. The method comprises the following steps: to a football match video highlight, defining whether a football video highlight clip can be separated into a football video event composed of a plurality of motions; constructing a core-surrounding event model to express a football highlight clip; utilizing football match video and corresponding text narration to construct a training set, selecting goals and red and yellow cards as two types of football highlights, and training the event model; inputting a segment of football match video without narration, identifying an appearance position of a football highlight clip in the input video, and giving a matching mark; according to a user requirement, automatically synthesizing a football highlight clip with a highest mark to be a football video highlight. According to a method of generating the football video highlight in the invention, restriction of factors such as a lens distance of the input video, and the method can be widely applied and popularized to fields of personal digital entertainment, physical education movie and television production and the like.

Description

technical field [0001] The invention relates to the fields of computer vision, video processing and augmented reality, in particular to a method for automatically synthesizing football video highlights based on an event model. Background technique [0002] As a kind of sports film and television program, sports video highlights are popular among audiences because they can obtain sufficient information in a relatively short period of time. Especially in football matches, it is very time-consuming to watch a 90-minute game video just to see a favorite player or a wonderful shot. Therefore, football match highlights are often used to record highlights, game summaries, and personal experiences of players. and other topics related to the competition. Traditional video highlights are edited by humans. Although the editing accuracy is high and full of emotion, it takes a lot of manpower to check the video frame by frame to find the desired highlights, and requires a high level of ...

AI Technical Summary

Problems solved by technology

[0007] To sum up, there are mainly two problems in the current video collection technology: (1) It depends heavily on the quality of the input video, and the scope of application is narrow

Using clues rich in semantic hints such as camera cuts, whistles, and transitions to make video highlights can quickly detect football highlight clips, but it is impossible to understand the progress of football events, so it is difficult to extract the time interval when the event occurred

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