Semantic Analysis of Soccer Video Using
Chung‐Lin Huang, Huang-Chia Shih, Chung-Yuan Chao · 2006
Video semantic analysis is formulated based on the low-level image features and the high-level knowledge which is en- coded in abstract, nongeometric representations. This paper intro- duces a semantic analysis system based on Bayesian network (BN) and dynamic Bayesian network (DBN). It is validated in the par- ticular domain of soccer game videos. Based on BN/DBN, it can identify the special events in soccer games such as goal event, corner kick event, penalty kick event, and card event. The video analyzer ex- tracts the low-level evidences, whereas the semantic analyzer uses BN/DBN to interpret the high-level semantics. Different from pre- vious shot-based semantic analysis approaches, the proposed se- mantic analysis is frame-based for each input frame, it provides the current semantics of the event nodes as well as the hidden nodes. Another contribution is that the BN and DBN are automatically generated by the training process instead of determined by ad hoc. The last contribution is that we introduce a so-called temporal in- tervening network to improve the accuracy of the semantics output. Index Terms—Dynamic Bayesian network (DBN), temporal in- tervening network (TIN), video semantic analysis.