In the recent times, the self-driving cars or the autonomous cars are getting more attention, as they are proved to be more convenient and require less human effort for travelling. The main things to be considered when driving are the traffic signals, the lane in which it moves and the surrounding environment which includes the pedestrians. The object detection is one of the main components in the autonomous cars. With the combination of the computer vision and machine learning, a system is built for the vehicle detection, lane detection and pedestrian detection. With this system using an ACF algorithm, the vehicle detection can be done and we also estimate the distance between the detected vehicle. The detection of the lane, vehicles and the pedestrians is achieved. The results are compared with the existing methods and are seen to be better than the existing methods.


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    Titel :

    Detection of Pedestrian, Lane and Traffic Signal for Vision Based Car Navigation


    Beteiligte:


    Erscheinungsdatum :

    21.05.2021


    Format / Umfang :

    307229 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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