关键词: 大型舰船舰面保障作业（FDASJ）, 复杂事件检测, 自动聚类, 带约束的聚类, 多实体贝叶斯网络（MEBN）

Abstract:

The Flight Deck Aviation Support Job（FDASJ） on the large ship is the preparatory work happening on the flight deck. The detection of FDASJ benefits to analyze and improve efficiency. During the action of the air fleet, the FDASJs are always performed for all of the aircrafts simultaneously, involving hundreds of operators, high level instruments and facilities. Aiming at the difficulties that to detect multi-FDASJs occurring in the same scene during the same time period, participants of which are located alternatively, it presents a FDASJs detection method based on Multi-entity Bayesian Network（MEBN）. In the first place, it obtains the clear trajectories for all the objects in the video during the preprocessing stage. In the FDASJ detection stage, with the input of the trajectories, it first performs the automatic constrained clustering algorithm to cluster the trajectories participating in the same FDASJ into the same cluster; then infers the type of the FDASJ inside each cluster using the FDASJ recognition algorithm based on MEBN. Experiments on the video data set captured from the flight deck demonstrate the effectiveness of the proposed method.

Key words: Flight Deck Aviation Support Job（FDASJ）, complex event detection, automatic clustering, constrained clustering, Multi-entity Bayesian Networks（MEBN）