Event boundary determination based on attack-defense transition analysis in soccer video

Abstract

Event detection is the key technology of content based sports video retrieval. Accurate detecting the boundaries of video events can effectively improve the user experience, and reduce the cost of video transmission. However, many existing works mainly focused on how to find the event, fewer on the determination of event boundary. In this work, we proposed an approach to determine the event boundary based on attackdefense transition analysis (ADTA) in soccer video. The main contributions of our work are as follows. A histogram based kickoff circle detection algorithm is proposed to facilitate the field zones partition. The proposed algorithm is fast and robust comparing with the existing methods. By the extracted mid-level features, the soccer playfield is divided into different zones, which imply different semantics in soccer game. Furthermore, the far view shot is segmented into sub-shots with captured zones, which benefit the highlight event and event boundary detection. The highlight events boundaries are accurately determined by attack-defense change points (ADCPs) detection combined with affection arousal curve. Experimental results demonstrated the effectiveness of the proposed approach.