We developed a real-time vehicle detection system combining YOLOX and Kalman filter tracking, optimized for 3D Light detection and ranging (LiDAR) data. Using a TigerCub Flash LiDAR camera, our method eliminates color variability, enhancing detection accuracy. The machine learning models were deployed on an NVIDIA Jetson Orin Nano, achieving over 95% precision in real-time at 30 frames-per-second.


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    Title :

    3D Flash LiDAR Object Detection and Tracking on Edge Hardware


    Contributors:


    Publication date :

    2024-07-15


    Size :

    617519 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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