Title :
Multiple Vehicles Detection and Tracking based on Scale-Invariant Feature Transform
Author :
Choi, Jae-Young ; Sung, Kyung-Sang ; Yang, Young-Kyu
Author_Institution :
Kyungwon Univ., Seongnam
fDate :
Sept. 30 2007-Oct. 3 2007
Abstract :
To monitor road situation, the source from CCTV is more useful than any other data from GPS or loop detector because it can give the whole picture of the two-dimensional traffic situation. This paper suggests multiple vehicles detection by quad-tree segmentation and tracking method using scale invariant feature transform to improve the performance of tracking for extracting traffic parameter such as vehicle count, speed, class, and so on. The experimental result presents the proposed method is effective and robust on detection and tracking vehicle, especially in cases that a vehicle changes a lane, occlusion of vehicles is occurred, and an affine shape of vehicle is changed due to car movement.
Keywords :
automated highways; feature extraction; image segmentation; object detection; optical tracking; quadtrees; road traffic; road vehicles; CCTV; GPS; feature extraction; intelligent transportation system; loop detector; multiple vehicles detection; optical tracking; quadtree segmentation; scale-invariant feature transform; traffic monitoring; Data mining; Detectors; Global Positioning System; Monitoring; Roads; Robustness; Shape; Tracking; Vehicle detection; Vehicles;
Conference_Titel :
Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-1396-6
Electronic_ISBN :
978-1-4244-1396-6
DOI :
10.1109/ITSC.2007.4357684