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.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Recognition Method of Airport Typical Motion Behavior Based on Infrared Image


    Beteiligte:
    Wu, Xiaozhou (Autor:in) / Ding, Meng (Autor:in) / Wang, Xuhui (Autor:in) / Li, Xu (Autor:in)


    Erscheinungsdatum :

    14.10.2020


    Format / Umfang :

    494574 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Typical small-city airport

    Schmidt, R.W.F. | Engineering Index Backfile | 1945


    Multi-aircraft behavior recognition method for airport scene based on ASTERIX data

    Wang, Kai / Li, Shengwei / Yue, Heng et al. | IEEE | 2024



    Aircraft image recognition in airport flight area based on deep transfer learning

    Yang, Lijun / Tao, Zheng | British Library Conference Proceedings | 2021