Soccer Highlight Detection using Two-Dependence Bayesian Network

Soccer highlight detection is an active research topic in recent years. One of the difficult problems is how to effectively fuse multi-modality cues, i.e. audio, visual and textual information, to improve the detection performance. This paper proposes a novel two-dependence Bayesian network (2dBN) based fusion approach to soccer highlight detection. 2dBN is a particular Bayesian network which assumes that each variable depends on two other variables at most. Through this assumption, 2d-BN can not only characterize the relationships among features but also be trained efficiently. Extensive experiments demonstrate the effectiveness of the proposed method.

• Type: Conference
• Year: 2006
• Where: ICMCS
• Authors: Jianguo Li, Tao Wang, Wei Hu, Mingliang Sun, Yimin Zhang
• Keywords: Bayesian Network, ICMCS 2006, Particular Bayesian Network, Two-dependence Bayesian Network