Scale Invariant Feature Transformed Based Vehicle Detection: A Review

International Journal of Computer & Organization Trends  (IJCOT)          
© 2015 by IJCOT Journal
Volume - 5 Issue - 5
Year of Publication : 2015
AuthorsSheetal Madhukar Parate, Prof. Kemal Koche


Sheetal Madhukar Parate, Prof. Kemal Koche "Scale Invariant Feature Transformed Based Vehicle Detection: A Review", International Journal of Computer & organization Trends (IJCOT), V5(5):1-9 Sep - Oct 2015, ISSN:2249-2593, Published by Seventh Sense Research Group.

Abstract Advanced driver assistance systems (ADAS) face many challenges in night-driving situations where due to poor illumination conditions the detection of other vehicles on the road becomes quite difficult. Traditional approaches attempt to use complex enhancement algorithms that consume a lot of computational power and are sensor dependent. This dissertation investigates the techniques for Scale-Invariant Feature Transform-based vehicle detection. A novel system that can heartily distinguish and track the development of vehicles in the video frames is proposed. The system consists of two noteworthy modules: a symmetry based item detector and a Kalman filter based vehicle tracker.


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Vehicle Detection, Scale invariant feature transform (SIFT), keypont.