A Review of Vision-Based Vehicle Detection and Tracking Techniques for Intelligent Vehicle
Authors
Mengxin Li, Xiangqian Tian, Ying Zhang, Ke Xu, Dai Zheng
Corresponding Author
Mengxin Li
Available Online April 2015.
- DOI
- 10.2991/isrme-15.2015.86How to use a DOI?
- Keywords
- Intelligent Vehicle; Machine Vision; Vehicle Detection; Vehicle Tracking
- Abstract
Vision-based vehicle detection and tracking techniques is of great importance to reduce vehicle collision accidents and increase the driving safety on road. This paper presents a comprehensive review of latest techniques for vehicle detection and tracking. In hypothesis generation of vehicles, motion-based, knowledge-based and stereo-vision based methods are introduced. Hypothesis verification includes template-based, appearance-based and multi-features fusion methods. In addition, three main algorithms are introduced in vehicle tracking. Finally, existing problems and future research directions of this field are summarized.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Mengxin Li AU - Xiangqian Tian AU - Ying Zhang AU - Ke Xu AU - Dai Zheng PY - 2015/04 DA - 2015/04 TI - A Review of Vision-Based Vehicle Detection and Tracking Techniques for Intelligent Vehicle BT - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering PB - Atlantis Press SP - 402 EP - 405 SN - 1951-6851 UR - https://doi.org/10.2991/isrme-15.2015.86 DO - 10.2991/isrme-15.2015.86 ID - Li2015/04 ER -