地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (7): 994-1008.doi: 10.12082/dpxxkx.2019.180697
方莉娜1,2,3(), 黄志文1,2,3, 罗海峰1,2,3, 陈崇成1,2,3
收稿日期:
2018-12-28
修回日期:
2019-03-13
出版日期:
2019-07-25
发布日期:
2019-07-25
作者简介:
作者简介:方莉娜(1983-),女,广西桂林人,博士,助理研究员,主要从事激光雷达数据处理与三维重建。E-mail: <email>fangln@fzu.ded.cn</email>
基金资助:
Li'na FANG1,2,3,*(), Zhiwen HUANG1,2,3, Haifeng LUO1,2,3, Chongcheng CHEN1,2,3
Received:
2018-12-28
Revised:
2019-03-13
Online:
2019-07-25
Published:
2019-07-25
Contact:
Li'na FANG
E-mail:fangln@fzu.ded.cn
Supported by:
摘要:
本文提出一种基于SVM与图匹配相结合的车载激光点云道路标线识别方法。该方法基于标线点云分割对象,利用Hu不变矩、实心形状上下文(SSC)、最小外包矩形(MBR)面积和延展度构建形状特征向量,采用SVM进行道路标线粗分类。针对粗分类结果,构建能够精确描述空间语义信息(如局部区域内标线间的排列、方向、距离)的图结构,通过图匹配方法优化粗分类结果,完成直行箭头、人行横道预告标识线、单向转向箭头、双向转向箭头、虚线型标线、斑马线共六类道路标线的精确识别。本文实验采用4份不同场景车载激光点云数据,实验结果中6类标线分类的准确率分别达100%、100%、94.12%、100%、94.94 %、99.25%,召回率分别达100%、100%、88.89%、100%、98.21%、99.00%,F1-Measure值分别达100%、100%、91.43%、100%、96.59%、99.12%。结果表明,本文方法能实现多类标线对象的精确识别,并对形状相似标线(如直行箭头、虚线型标线与斑马线)的区分具有较强稳健性。
方莉娜, 黄志文, 罗海峰, 陈崇成. 结合SVM与图匹配的车载激光点云道路标线识别[J]. 地球信息科学学报, 2019, 21(7): 994-1008.DOI:10.12082/dpxxkx.2019.180697
Li'na FANG, Zhiwen HUANG, Haifeng LUO, Chongcheng CHEN. Integrating SVM and Graph Matching for Identifying Road Markings from Mobile LiDAR Point Clouds[J]. Journal of Geo-information Science, 2019, 21(7): 994-1008.DOI:10.12082/dpxxkx.2019.180697
表7
Yu方法与本文方法标线分类对比精度"
方法 | 类别 | 精度/ % | 召回率/ % | F1-Measure/% |
---|---|---|---|---|
Yu方法[ | 直行箭头 | 75 | 100 | 85 |
人行横道预告标识线 | 100 | 100 | 100 | |
单向转向箭头 | 88.89 | 88.89 | 88.89 | |
双向转向箭头 | 100 | 100 | 100 | |
虚线型标线 | 93.24 | 97.89 | 95.51 | |
斑马线 | 99.46 | 92.73 | 95.97 | |
本文方法 | 直行箭头 | 100 | 100 | 100 |
人行横道预告标识线 | 100 | 100 | 100 | |
单向转向箭头 | 94.12 | 88.89 | 91.43 | |
双向转向箭头 | 100 | 100 | 100 | |
虚线型标线 | 94.94 | 98.21 | 96.59 | |
斑马线 | 99.25 | 99.00 | 99.12 |
[1] | Wu T, Ranganathan A.A practical system for road marking detection and recognition[C]. Intelligent Vehicles Symposium, 2012:25-30. |
[2] |
Mathibela B, Newman P, Posner I.Reading the road: Road marking classification and interpretation[J]. IEEE Transactions on Intelligent Transportation Systems, 2015,16(4):2072-2081.
doi: 10.1109/TITS.2015.2393715 |
[3] | Danescu R, Nedevschi S.Detection and classification of painted road objects for intersection assistance applications[C]. International IEEE Conference on Intelligent Transportation Systems, 2010:433-438. |
[4] |
Guan H, Li J, Yu Y, et al.Using mobile laser scanning data for automated extraction of road markings[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014,87:93-107.
doi: 10.1016/j.isprsjprs.2013.11.005 |
[5] |
Guan H, Li J, Yu Y, et al.Using mobile LiDAR data for rapidly updating road markings[J]. IEEE Transactions on Intelligent Transportation Systems, 2015,16(5):2457-2466.
doi: 10.1109/TITS.2015.2409192 |
[6] |
Guan H, Li J, Yu Y, et al.Automated road information extraction from mobile laser scanning data[J]. IEEE Transactions on Intelligent Transportation Systems, 2015,16(1):194-205.
doi: 10.1109/TITS.2014.2328589 |
[7] | Chen X, Kohlmeyer B, Stroila M, et al.Next generation map making:geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extraction[C]. ACM Sigspatial International Symposium on Advances in Geographic Information Systems, Acm-Gis 2009, November 4-6, 2009, Seattle, Washington, Usa, Proceedings, 2009:488-491. |
[8] | Riveiro B, González-Jorge H, Martínez-Sánchez J, et al.Automatic detection of zebra crossings from mobile LiDAR data[J]. Optics & Laser Technology, 2015,70:63-70. |
[9] |
Cheng M, Zhang H, Wang C, et al.Extraction and classification of road markings using mobile laser scanning point clouds[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017,10(3):1182-1196.
doi: 10.1109/JSTARS.2016.2606507 |
[10] | Yang M, Wan Y, Liu X, et al.Laser data based automatic recognition and maintenance of road markings from MLS system[J]. Optics & Laser Technology, 2018,107:192-203. |
[11] |
Jaakkola A, Hyyppä J, Hyyppä H, et al.Retrieval algorithms for road surface modelling using laser-based mobile mapping[J]. Sensors, 2008,8(9):5238.
doi: 10.3390/s8095238 |
[12] | Mancini A, Frontoni E, Zingaretti P.Automatic road object extraction from Mobile Mapping Systems[C]. Ieee/asme International Conference on Mechatronics and Embedded Systems and Applications, 2012:281-286. |
[13] | Yang B, Fang L, Li Q, et al.Automated extraction of road markings from mobile LIDAR point clouds[J]. Photogrammetric Engineering & Remote Sensing, 2012,78(4):331-338. |
[14] |
Yu Y, Li J, Guan H, et al.Learning hierarchical features for automated extraction of road markings from 3-D mobile LiDAR point clouds[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015,8(2):709-726.
doi: 10.1109/JSTARS.2014.2347276 |
[15] |
Soilán M, Riveiro B, Martínez-Sánchez J, et al.Segmentation and classification of road markings using MLS data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017,123:94-103.
doi: 10.1016/j.isprsjprs.2016.11.011 |
[16] | Hervieu A, Soheilian B, Brédif M. Road marking extraction using a model& data-Driven Rj-Mcmc[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015,II-3/W4:47-54. |
[17] |
Yang B, Fang L, Li J.Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013,79:80-93.
doi: 10.1016/j.isprsjprs.2013.01.016 |
[18] | Hu M.Visual pattern recognition by moment invariants[J]. Information Theory Ire Transactions on, 1962,8(2):179-187. |
[19] |
Premachandran V, Kakarala R.Perceptually motivated shape context which uses shape interiors[J]. Pattern Recognition, 2013,46(8):2092-2102.
doi: 10.1016/j.patcog.2013.01.030 |
[20] | 罗海峰,方莉娜,陈崇成.车载激光扫描数据路坎点云提取方法[J].地球信息科学学报,2017,19(7):861-871. |
[ Luo H F, Fang L N, Chen C C.Curb point clouds extraction from vehicle-borne laser scanning data[J]. Journal of Geo-information Science, 2017,19(7):861-871. ] | |
[21] |
彭晨,余柏蒗,吴宾,等.基于移动激光扫描点云特征图像和SVM的建筑物立面半自动提取方法[J].地球信息科学学报,2016,18(7):878-885.
doi: 10.3724/SP.J.1047.2016.00878 |
[ Peng C, Yu B L, Wu B, et al.A method for semiautomated segmentation of building facade from mobile laser scanning point cloud based on feature images and SVM[J]. Journal of Geo-information Science, 2016,18(7):878-885. ]
doi: 10.3724/SP.J.1047.2016.00878 |
|
[22] |
熊伟成,杨必胜,董震.面向车载激光扫描数据的道路目标精细化鲁棒提取[J].地球信息科学学报,2016,18(3):376-385.
doi: 10.3724/SP.J.1047.2016.00376 |
[ Xiong W C, Yang B C, Dong Z.Refining and robust extraction of roads from mobile laser scanning point clouds[J]. Journal of Geo-information Science, 2016,18(3):376-385. ]
doi: 10.3724/SP.J.1047.2016.00376 |
|
[23] | Foggia P, Percannella G, Vento M.Graph matching and learning in pattern recognition in the last 10 years[J]. International Journal of Pattern Recognition & Artificial Intelligence, 2014,28(1):1450001. |
[24] | 项英倬,谭菊仙,韩杰思,等.图匹配技术研究[J].计算机科学,2018,45(6):33-37,51. |
[Xiang Y Z, Tan J X, Han J S. Survey of graph matching algorithms[J]. Computer Science, 2018,45(6):33-37,513. ]. | |
[25] | Hartley R, Zisserman A.Multiple view geometry in computer vision[M]. UK: Gambridge University Press,2003. |
[26] | Szegedy C, Vanhoucke V, Ioffe S, et al.Rethinking the Inception Architecture for Computer Vision[C]. Computer Vision and Pattern Recognition, 2016:818-2826. |
[27] |
Wold S.Pattern recognition by means of disjoint principal components models[J]. Pattern Recognition, 1976,8(3):127-139.
doi: 10.1016/0031-3203(76)90014-5 |
[28] |
陈占龙,周林.基于方向关系矩阵的空间方向相似性定量计算方法[J].测绘学报,2015,44(7):813-821.
doi: 10.11947/j.AGCS.2015.20140198 |
[ Chen Z L, Zhou L, et al. A quantitative calculation method of spatial direction similarity based on direction relation matrix[J]. Acta Geodaetica et Cartographica Sinica, 2015,44(7):813-821.].
doi: 10.11947/j.AGCS.2015.20140198 |
|
[29] | Dekel T, Oron S, Rubinstein M, et al.Best-Buddies Similarity for robust template matching[C]. Computer Vision and Pattern Recognition, 2015.2021-2029. |
[30] | 王刚,孙晓亮,尚洋,等.一种基于最佳相似点对的稳健模板匹配算法[J].光学学报,2017(3):274-280. |
[ Wang G, Sun X L, S Y,et al. A robust template matching algorithm based on eest-buddies similarity[J]. Acta Optica Sinica,2017(3):274-280. ] | |
[31] |
Dangerfield J.Linear programming and its applications by J. K. Strayer[J]. Mathematical Gazette,1990,74(470):402-403.
doi: 10.2307/3618167 |
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