Abstract：To solve the problem that the traditional complex video event detection methods could not effectively use the semantic concept information, the complex event detection method was proposed based on the combination of semantic concept and twostream feature model. The motion detector and the object concept detector were employed to obtain dynamic concepts and static concepts. A method of generating optimal concept subsets for tasks was proposed to construct the video event detector according to the preferred concept subset. Combined with the twostream feature and LSTM, the results of event analysis and expression model were fused and classified. The event classification analysis results respectively based on the semantic concept and the dualstream model were merged with decisionmaking to detect complex events. The proposed algorithm was compared with the related algorithms on the typical complex event dataset. The results show that the proposed method is modified substantially with accuracy rate of 81.1%, which is 5.7% higher than that of the optimal algorithm.
