Unmanned aerial vehicles with high quality video cameras are able to provide videos from 50,000 feet up that show a surprising amount of detail on the ground. These videos are difficult to analyze, because the airplane moves, the camera zooms in and out and vibrates, and the moving objects of interest can be in the scene, out of the scene, or partly occluded. Recognizing both the moving and static objects is important in order to find events of interest to human analysts. In this paper, we describe our approach to object and event recognition using multiple stages of classification.


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    Titel :

    Object and event recognition for aerial surveillance


    Beteiligte:
    Li, Yi (Autor:in) / Atmosukarto, Indriyati (Autor:in) / Kobashi, Masaharu (Autor:in) / Yuen, Jenny (Autor:in) / Shapiro, Linda G. (Autor:in)

    Kongress:

    Optics and Photonics in Global Homeland Security ; 2005 ; Orlando,Florida,United States


    Erschienen in:

    Erscheinungsdatum :

    2005-05-19





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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