Abstract
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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The research is supported by Science Engineering Research Board, under startup Research Grant Program in Engineering Science with File NO.: SERB/SRG/2019/002277 and is gratefully acknowledged.
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Anandhalli, M., Tanuja, A., Baligar, V.P., Baligar, P., Saraf, S.S. (2022). Vehicle Detection and Tracking Based on Interest Points of Visual Appearance. In: Bhaumik, S., Chattopadhyay, S., Chattopadhyay, T., Bhattacharya, S. (eds) Proceedings of International Conference on Industrial Instrumentation and Control. Lecture Notes in Electrical Engineering, vol 815. Springer, Singapore. https://doi.org/10.1007/978-981-16-7011-4_35
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DOI: https://doi.org/10.1007/978-981-16-7011-4_35
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