Paper Info
Title
Multi-camera vehicle identification in tunnel surveillance system
Abstract
Tunnel traffic security has received increasing attention since accidents in tunnels may cause serious casualties. Surveillance cameras are widely equipped in tunnels for traffic condition monitoring and safety maintenance. Vehicle identification among multiple cameras is an essential component in tunnel surveillance systems. In this paper, we propose a Spatiotemporal Successive Dynamic Programming (S2DP) algorithm for identifying vehicles between pairs of cameras. Taking color information into consideration, we extract features based on Harris corner detection with OpponentSIFT descriptors. “Tracking-by-identification” for vehicles across multiple cameras can thus be achieved. Extensive experiments on real tunnel video data show that the proposed S2DP algorithm outperforms state-of-the-art methods.
Year
DOI
Venue
2015
10.1109/ICMEW.2015.7169793
ICME Workshops
Keywords
Field
DocType
Intelligent transportation system, video surveillance, tunnel surveillance, multi-camera tracking, vehicle identification
Computer vision,Dynamic programming,Multi camera,Vehicle identification,Corner detection,Computer science,Multi camera tracking,Vehicle dynamics,Artificial intelligence,Intelligent transportation system,Traffic conditions
Conference
ISSN
Citations 
PageRank 
2330-7927
0
0.34
References 
Authors
23
5
Name
Order
Citations
PageRank
Hua-Tsung Chen128928.72
Ming-Chu Chu200.34
Chien-Li Chou38610.09
Suh-Yin Lee41596319.67
Bao-Shuh Paul Lin57818.71