標題: Efficient Road Lane Marking Detection with Deep Learning
作者: Chen, Ping-Rong
Lo, Shao-Yuan
Hang, Hsueh-Ming
Chan, Sheng-Wei
Lin, Jing-Jhih
交大名義發表
National Chiao Tung University
關鍵字: semantic segmentation;lane detection;dilated convolution;deep convolutional neural networks
公開日期: 1-Jan-2018
摘要: Lane mark detection is an important element in the road scene analysis for Advanced Driver Assistant System (ADAS). Limited by the onboard computing power, it is still a challenge to reduce system complexity and maintain high accuracy at the same time. In this paper, we propose a Lane Marking Detector (LMD) using deep convolutional neural network to extract robust lane marking features. To improve its performance with a target of lower complexity, the dilated convolution is adopted. A shallower and thinner structure is designed to decrease the computational cost. Moreover, we also design post-processing algorithms to construct 3rd-oder polynomial models to fit into the curved lanes. Our system shows promising results on the captured road scenes.
URI: http://hdl.handle.net/11536/151061
ISSN: 1546-1874
期刊: 2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP)
Appears in Collections:Conferences Paper