Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Lane Line Detection based on Mask R-CNN

Authors
Bin Liu, Hongzhe Liu, Jiazheng Yuan
Corresponding Author
Bin Liu
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.111How to use a DOI?
Keywords
lane detection; deep learning; the diversity of samples; Mask R-CNN.
Abstract
Lane detection plays an important role in driverless system. However, the complexity of the actual road environment makes lane detection more challenging. In recent years, the rapid development of deep learning has pointed out the direction to solve this problem. Deep learning does not care about the change of environment, but only about the diversity of samples. As long as enough samples are trained, the target can be detected and identified. Based on this, a lane detection algorithm based on Mask R-CNN is proposed, which can not only detect lane quickly, but also reach to a total 97.9% of accuracy on our TSD-Max datasets.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.111How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Bin Liu
AU  - Hongzhe Liu
AU  - Jiazheng Yuan
PY  - 2019/04
DA  - 2019/04
TI  - Lane Line Detection based on Mask R-CNN
BT  - 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.111
DO  - https://doi.org/10.2991/icmeit-19.2019.111
ID  - Liu2019/04
ER  -