@inproceedings{b038938eca4d4d8d9125a0f2970e4f04,
title = "A multiple-lane vehicle tracking method for forward collision warning system applications",
abstract = "This paper proposes a vehicle tracking method for the Forward Collision Warning System (FCWS). The proposed method applies vehicle detection and feature tracking to each frame in the videos to enhance the detection accuracy and increase the stability of vehicle localization. The proposed method can be applied to three-lane FCWS which includes left, main, and right lanes. The performance of the proposed three-lane FCWS can achieve 720×480 video@183 fps in average when realized in PC with Intel Core i7 processor with average detection accuracy of 94.05\% at daytime and 86.90\% at night. The proposed method is also implemented on Freescale i.MX6 embedded platform with a USB webcam to capture the video. Under the D1 (720×480) resolution, the performance of the proposed 3-lane FCWS can achieve 29 fps.",
author = "Li, \{Yuan Fu\} and Tsai, \{Chia Chi\} and Lai, \{Yi Ting\} and Guo, \{Jiun In\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/APSIPA.2017.8282185",
language = "English",
series = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1061--1064",
booktitle = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",
address = "United States",
}