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%.
Vehicle Detection and Tracking Based on Interest Points of Visual Appearance
Lect. Notes Electrical Eng.
Proceedings of International Conference on Industrial Instrumentation and Control ; Kapitel : 35 ; 351-362
15.02.2022
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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