The Flight Deck Aviation Support Job (FDASJ) on the large ship cover all the activities happening during the period from the airplane landing on the ship to the airplane taking off from the ship. It has been a challenge problem to detect the FDASJ based on videos. The difficulty is to detect multi-FDASJs occurring in the same scene during the same time period, participants of which are located alternatively. In this study, we propose an FDASJ detection method based on video event. The FDASJ is represented as the complex event composed of the fine-grained FDASJs. The FDASJ structure extraction algorithm based on trajectory hierarchical clustering is first adopted to determine the hierarchical combination relationship between FDASJs and the participators of each FDASJ; the FDASJ identification algorithm based on activity model is performed to identify the FDASJs. Experimental results show that the proposed method achieves sound performance and could detect multi-FDASJs occurring in the same scene during the same time period, participants of which are located alternatively.