Accurate localization and recognition of objects in the three dimensional (3D) space can be useful in security and defence applications such as scene monitoring and surveillance. A main challenge in 3D object localization is to find the depth location of objects. We demonstrate here the use of a camera array with computational integral imaging to estimate depth locations of objects detected and classified in a two-dimensional (2D) image. Following an initial 2D object detection in the scene using a pre-trained deep learning model, a computational integral imaging is employed within the detected objects’ bounding boxes, and by a straightforward blur measure analysis, we estimate the objects’ depth locations.


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    Titel :

    Efficient depth localization of objects in a 3D space using computational integral imaging


    Beteiligte:
    Bouma, Henri (Herausgeber:in) / Dijk, Judith (Herausgeber:in) / Prabhu, Radhakrishna (Herausgeber:in) / Stokes, Robert J. (Herausgeber:in) / Yitzhaky, Yitzhak (Herausgeber:in) / Kadosh, Michael (Autor:in) / Fraiman, Anton (Autor:in) / Peli, Eli (Autor:in) / Yitzhaky, Yitzhak (Autor:in)

    Kongress:

    Artificial Intelligence for Security and Defence Applications ; 2023 ; Amsterdam, Netherlands


    Erschienen in:

    Proc. SPIE ; 12742


    Erscheinungsdatum :

    2023-10-17





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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