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Recognition Method of Airport Typical Motion Behavior Based on Infrared Image

Aiming at the problem of airport surface behavior recognition in low illuminance environment, based on infrared monitoring image data, the eco (efficient fluctuation operators for tracking) target tracking method is proposed to track different targets on airport surface including non-cooperative targets. The method of extracting macro motion features from tracking results is studied. On this basis, the long-term motion features are learned recursively in the framework of LSTM (long short term memory) network to realize the recognition of typical human actions on the airport surface. The experimental results on the self-made video data set show that the model can make full use of the long-term motion information in the video sequence. It is suitable for the airport scene in low illumination environment, and has a certain recognition effect.