Anti-Collision Warning Algorithm based on Visual Perception in Front of Vehicle

DOI

10.2991/mecae-17.2017.9How to use a DOI?

Keywords

Computer Vision, Pattern Recognition, Rear-End Collision Warning

Abstract

The vehicles' driving safety plays an important role in the transportation safety's development, and it's a necessary requirement in intelligent transportation and intelligent vehicle. The point that is suggested in this paper is that vehicles' collision warning system which is based on computer vision, and the system is built on computer vision, pattern recognition, machine learning and some other artificial intelligent theory and techniques, discerning the vehicles which is in front of your vehicle and measure the security range, warning the possible danger timely to make sure your drive safe. We use the characteristic which is called haar of the samples to train in the classifier to get a cascaded classifier named Boosted, loading the classifier and image of the vehicles marked and calculating the distance and relative speed. In the last, we do a lot of system simulation experiments, verifying the accuracy and the effectiveness of the system from vehicle outline detection results and safe vehicle determination.

Copyright

© 2017, 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/).

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TY  - CONF
AU  - Pengheng Ding
AU  - Jindong Zhang
AU  - Yanghao Zhou
AU  - Hongliang Liu
AU  - Xiao Wang
PY  - 2017/03
DA  - 2017/03
TI  - Anti-Collision Warning Algorithm based on Visual Perception in Front of Vehicle
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 51
EP  - 55
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.9
DO  - 10.2991/mecae-17.2017.9
ID  - Ding2017/03
ER  -