DocumentCode
1868154
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
fYear
2007
fDate
Sept. 30 2007-Oct. 3 2007
Firstpage
528
Lastpage
533
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ITSC.2007.4357684
Filename
4357684
Link To Document