@inproceedings{45d21545cfab441992263a20250ca0d2,
title = "Real-time driver assistance systems via dual camera stereo vision",
abstract = "This paper presents the practical application for a real-time and image-based driver assistance system. Dual-camera stereo vision algorithm for the distance measurement for the detected vehicle and multi-line merge function for the lane detection are implemented via lab-made library and calibrated off-line. A lab-made library developed via programming language is written and compiled for low computing-power consumption and rapidly calculating for the real-time purpose. To save the computing power consumption, some proper region of interest of vehicle detection and lane detection are applied. Finally, this system has been preliminary implemented on a test vehicle and driven on various roads over tens of miles and reach around 4 5 frame per seconds via portable embedded system.",
author = "Sie, {Yong Da} and Tsai, {Yi Cheng} and Lee, {Wei Hsun} and Chou, {Chien Ming} and Chiu, {Chi Yi}",
note = "Funding Information: ACKNOWLEDGMENT The authors acknowledge the support of the Ministry of Science and Technology of the Republic of China, Taiwan, under Grant MOST 106-2634-F-006-002 -CC2 and MOST 108-2119-M-006-006 -. Publisher Copyright: {\textcopyright} 2019 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 89th IEEE Vehicular Technology Conference, VTC Spring 2019 ; Conference date: 28-04-2019 Through 01-05-2019",
year = "2019",
month = apr,
doi = "10.1109/VTCSpring.2019.8746289",
language = "English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings",
address = "United States",
}