This paper presents an approach for automatic annotation of soccer video based on the semantic events occurred inside it. The goal of this paper is to propose a flexible system that can be able to be used with minimum reliance on predefined patterns in event detection process. To achieve this goal, we propose a fuzzy inference system (FIS) implemented in the framework of an adaptive neural network which combines the self-learning capability of neural networks with explicit knowledge representation and precision of fuzzy based classification systems. This method provides the capability for fuzzy systems to learn information about a set of data in order to determine the parameters of membership functions (MFs) automatically and generate a set of fuzzy rules that best allow the FIS to track the input/output data. The proposed method is multimodal and employs statistical information from a set of audiovisual features that are organized in a hierarchical structure as input and produces semantic concepts corresponding to the occurred events. Experimental results conducted on a large set of soccer videos demonstrate the effectiveness of the proposed approach.
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