Discovering where a driver looks and what they look at while driving can provide many benefits to improve driving safety in Advanced Driver Assistance Systems (ADAS). Toward this goal, we utilized a research vehicle equipped with a remote gaze tracker installed inside the vehicle and facing the driver and a LiDAR mounted on the roof of the vehicle. We introduce a novel approach for the cross-calibration of the gaze tracker with the LiDAR's system. We also propose a method to estimate the driver's Point of Gaze in the sparse LiDAR point cloud. In order to provide more information about the driver's attention, we introduce a technique to calculate the driver's visual attention area in the 3D space. We empirically demonstrate that our proposed multi-depth calibration-calibration approach yields excellent results to find the transformation matrix between a remote gaze tracker and LiDAR coordinate systems.


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    Titel :

    Multi-Depth Cross-Calibration of Gaze Tracker and LiDAR Systems


    Beteiligte:


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    8418372 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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