In recent years, the introduction of augmented reality in ADAS has become an active research topic. Such a system contributes to a more controllable, comfortable, and safe driving in the city. The surround view is one such system, which could be expanded by artificial intelligence. This paper presents one approach to designing a real-time surround view multi-camera system on Jetson Tegra TX2. The algorithm for finding intrinsic and extrinsic camera parameters based on compute homography matrix from descriptors of feature points was implemented on CPU and computing only once. To achieve real-time, the algorithms of geometric, photometric alignment and blending were implemented on GPU and use CUDA technology. Texture mapping on 3D bowl mesh using OpenGL ES. A virtual camera is used to achieve a 360° view. Experiment results show a surround view system with a good stitched quality and acceptable performance. Further development of the research project is presented.


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    Titel :

    Real-Time 3D Surround View System for Vehicle Based on Panoramic Stitching Image


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Guda, Alexander (Herausgeber:in) / Gasparyan, Sokrat (Autor:in) / Vasilianov, Georgii (Autor:in)

    Kongress:

    International School on Neural Networks, Initiated by IIASS and EMFCSC ; 2022 ; St.Petersburg, Russia February 08, 2022 - February 10, 2022



    Erscheinungsdatum :

    16.11.2022


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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