@inproceedings{bea5936adb3c45b7aa0377ccecee8312,
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.",
keywords = "Intelligent transportation system, multi-camera tracking, tunnel surveillance, Vehicle identification, video surveillance",
author = "Chen, {Hua Tsung} and Chu, {Ming Chu} and Chou, {Chien Li} and Lee, {Suh Yin} and Bao-Shuh Lin ",
year = "2015",
month = jul,
day = "28",
doi = "10.1109/ICMEW.2015.7169793",
language = "English",
series = "2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015",
address = "United States",
note = "2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015 ; Conference date: 29-06-2015 Through 03-07-2015",
}