DocumentCode :
2528132
Title :
Long-term Trajectory Extraction for Moving Vehicles
Author :
Xu, Jie ; Ye, Getian ; Zhang, Jian
Author_Institution :
New South Wales Univ., Sydney
fYear :
2007
fDate :
1-3 Oct. 2007
Firstpage :
223
Lastpage :
226
Abstract :
In recent years, trajectory analysis of moving vehicles in video-based traffic monitoring systems has drawn the attention of many researchers. Trajectory extraction is a fundamental step that is required prior to trajectory analysis. Lots of previous work have focused on trajectory extraction via tracking. However, they often fail to achieve long-term consistent trajectories. In this paper, we propose a robust approach for extracting long-term trajectories of moving vehicles in traffic monitoring using SIFT-descriptor. Experimental results show that the proposed method outperforms tracking-based techniques.
Keywords :
feature extraction; road traffic; video signal processing; SIFT desciiptor; long-term trajectory extraction; moving vehicles; scale invariant feature transform; video-based traffic monitoring systems; Australia Council; Automotive engineering; Computer science; Computerized monitoring; Condition monitoring; Karhunen-Loeve transforms; Robustness; Traffic control; Trajectory; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Signal Processing, 2007. MMSP 2007. IEEE 9th Workshop on
Conference_Location :
Crete
Print_ISBN :
978-1-4244-1274-7
Type :
conf
DOI :
10.1109/MMSP.2007.4412858
Filename :
4412858
Link To Document :
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