This paper presents a unique pattern of vehicle detection with the help of fundamental and successive algorithms. The characteristics of the vehicle are the important parameters to identify vehicles. A good number of corner points is compacted inside a vehicle region which is considered as the initial requirement for an algorithm. The densely packed corner points are grouped. This grouping gives a hint of points which are associated with each vehicle and they play a key in detection of vehicles. Once the grouping is performed, the non-vehicle region is segmented. The corner points are tracked with a Lucas-Kanade algorithm in order to maintain the stability of corner points. The detection rate with the proposed method is 93.95%.


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    Title :

    Vehicle Detection and Tracking Based on Interest Points of Visual Appearance


    Additional title:

    Lect. Notes Electrical Eng.




    Publication date :

    2022-02-15


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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