一、GitHub:
https://github.com/ChengZhongShen/Advanced_Lane_Lines
https://github.com/MaybeShewill-CV/lanenet-lane-detection
https://github.com/kky-fury/Lane_Detection
二、知乎:
无人驾驶-车道检测 https://zhuanlan.zhihu.com/p/46146266
三、文献
SCNN车道线检测--(SCNN)Spatial As Deep: Spatial CNN for Traffic Scene Understanding(论文解读)
https://www.cnblogs.com/guoyaohua/p/8940871.html?utm_source=tuicool&utm_medium=referral
【论文笔记】 Towards End-to-End Lane Detection: an Instance SegmentationApproach
https://blog.csdn.net/ctfabc4425/article/details/80887259
Lanenet 车道线检测网络模型学习(论文解读)
https://blog.csdn.net/c20081052/article/details/80622722
无人驾驶汽车系统入门(十二)——卷积神经网络入门,基于深度学习的车辆实时检测
https://blog.csdn.net/adamshan/article/details/79193775
车辆检测和车道检测
https://blog.csdn.net/weixin_37762749/article/details/80785137
A LOOK AT IMAGE SEGMENTATION USING CNNS
车道检测源码分析系列(一)
http://www.voidcn.com/article/p-yczjfjvv-pd.html
四、数据集
https://xingangpan.github.io/projects/CULane.html
五、车道线拟合算法
随机抽样一致 RANSAC(转) https://www.cnblogs.com/cfantaisie/archive/2011/06/09/2076864.html
Python闲谈(二)聊聊最小二乘法以及leastsq函数 https://www.cnblogs.com/NanShan2016/p/5493429.html
六、跟踪算法
详解卡尔曼滤波原理https://blog.csdn.net/u010720661/article/details/63253509
卡尔曼滤波 -- 从推导到应用(一)https://blog.csdn.net/heyijia0327/article/details/17487467
理解Kalman滤波的使用 http://www.cnblogs.com/jcchen1987/p/4371439.html
七、Demo
八、学习网址
九、CSDN
opencv车道线检测 https://blog.csdn.net/chongshangyunxiao321/article/details/50999212
车道线检测霍夫直线检测原理分析https://blog.csdn.net/happy_stars_2016/article/details/52691255
opencv 车道线检测(二)https://blog.csdn.net/fate_fjh/article/details/52921894
十、提取骨架算法
Hilditch's Algorithm for Skeletonization http://cgm.cs.mcgill.ca/~godfried/teaching/projects97/azar/skeleton.html#algorithm
OpenCV学习(15) 细化算法(3) https://www.cnblogs.com/mikewolf2002/p/3327183.html