車道線檢測參考學習資料
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:
無人駕駛-車道檢測 https://zhuanlan.zhihu.com/p/46146266
三、文獻
SCNN車道線檢測--(SCNN)Spatial As Deep: Spatial CNN for Traffic Scene Understanding(論文解讀)
https://www.cnblogs.com/guoyaohua/p/8940871.html?utm_source=tuicool&utm_medium=referral
【論文筆記】 Towards End-to-End Lane Detection: an Instance SegmentationApproach
https://blog.csdn.net/ctfabc4425/article/details/80887259
Lanenet 車道線檢測網路模型學習(論文解讀)
https://blog.csdn.net/c20081052/article/details/80622722
無人駕駛汽車系統入門(十二)——卷積神經網路入門,基於深度學習的車輛實時檢測
https://blog.csdn.net/adamshan/article/details/79193775
車輛檢測和車道檢測
https://blog.csdn.net/weixin_37762749/article/details/80785137
A LOOK AT IMAGE SEGMENTATION USING CNNS
車道檢測原始碼分析系列(一)
http://www.voidcn.com/article/p-yczjfjvv-pd.html
四、資料集
https://xingangpan.github.io/projects/CULane.html
五、車道線擬合算法
隨機抽樣一致 RANSAC(轉) https://www.cnblogs.com/cfantaisie/archive/2011/06/09/2076864.html
Python閒談(二)聊聊最小二乘法以及leastsq函式 https://www.cnblogs.com/NanShan2016/p/5493429.html
六、跟蹤演算法
詳解卡爾曼濾波原理https://blog.csdn.net/u010720661/article/details/63253509
卡爾曼濾波 -- 從推導到應用(一)https://blog.csdn.net/heyijia0327/article/details/17487467
理解Kalman濾波的使用 http://www.cnblogs.com/jcchen1987/p/4371439.html
七、Demo
八、學習網址
九、CSDN
opencv車道線檢測 https://blog.csdn.net/chongshangyunxiao321/article/details/50999212
車道線檢測霍夫直線檢測原理分析https://blog.csdn.net/happy_stars_2016/article/details/52691255
opencv 車道線檢測(二)https://blog.csdn.net/fate_fjh/article/details/52921894
十、提取骨架演算法
Hilditch's Algorithm for Skeletonization http://cgm.cs.mcgill.ca/~godfried/teaching/projects97/azar/skeleton.html#algorithm
OpenCV學習(15) 細化演算法(3) https://www.cnblogs.com/mikewolf2002/p/3327183.html