- About EITEE
- Articles Online
- For Authors
- For Reviewers
- Features
- Subscription & Service
- Personal Center
- Logout
FOLLOWUS
- About EITEE
- Introduction
- Editorial Board
- Corresponding Experts
- Events
- Honors
- Contact Us
- Articles Online
- Current Issue
- Archive
- Special Issues
- Virtual Issues
- Highlights
- In Press
- For Authors
- Submit
- Call for papers
- Guide for Authors
- Ethics & Disclosures
- Fee & Funding
- Downloads
- For Reviewers
- Guide for Reviewers
- Ethics & Disclosures
- Thanks card
- Features
- FITEE Forum
- Engineering Front
- Paper Videos
- Editors’ Corner
- Other Resources
- Subscription & Service
- Subscription
- Services
Road model prediction based unstructured road detection
- Road model prediction based unstructured road detection
- Frontiers of Information Technology & Electronic Engineering Vol. 14, Issue 11, Pages: 822-834(2013)
- Affiliations：
1.Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
2.Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China
- Author bio：
Tuo-zhong YAO, E-mail: thomasyao@zju.edu.cn
- Funds：
DOI：10.1631/jzus.C1300090
CLC： TP317.4;TP391Received：14 April 2013，
Revised：2013-10-15，
Published：2013-11
- Accepted：
Scan QR Code
Wen-hui ZUO, Tuo-zhong YAO. Road model prediction based unstructured road detection[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(11): 822-834.
Wen-hui ZUO, Tuo-zhong YAO. Road model prediction based unstructured road detection[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(11): 822-834. DOI： 10.1631/jzus.C1300090.
摘要
Abstract
Vision-based road detection is an important research topic in different areas of computer vision such as the autonomous navigation of mobile robots. In outdoor unstructured environments such as villages and deserts
the roads are usually not well-paved and have variant colors or texture distributions. Traditional region- or edge-based approaches
however
are effective only in specific environments
and most of them have weak adaptability to varying road types and appearances. In this paper we describe a novel top-down based hybrid algorithm which properly combines both region and edge cues from the images. The main difference between our proposed algorithm and previous ones is that
before road detection
an off-line scene classifier is efficiently learned by both low- and high-level image cues to predict the unstructured road model. This scene classification can be considered a decision process which guides the selection of the optimal solution from region- or edge-based approaches to detect the road. Moreover
a temporal smoothing mechanism is incorporated
which further makes both model prediction and region classification more stable. Experimental results demonstrate that compared with traditional region- and edge-based algorithms
our algorithm is more robust in detecting the road areas with diverse road types and varying appearances in unstructured conditions.
关键词
Keywords
references
Y. Alon , , , A. Ferencz , , , A. Shashua . . Off-Road Path Following Using Region Classification and Geometric Projection Constraints . . IEEE Conf. on Computer Vision and Pattern Recognition , , 2006 . . p.689 - - 696 . . . .
J.M. Alvarez , , , A.M. Lopez , , , R. Baldrich . . Illuminant Invariant Model-Based Road Segmentation . . Proc. IEEE Intelligent Vehicles Symp. , , 2008 . . p.1175 - - 1180 . . . .
J.M. Alvarez , , , T. Gevers , , , A.M. Lopez . . Vision-Based Road Detection Using Road Model . . 16th IEEE Int. Conf. on Image Processing , , 2009 . . p.2073 - - 2076 . . . .
J.M. Alvarez , , , T. Gevers , , , A.M. Lopez . . 3D Scene Priors for Road Detection . . IEEE Conf. on Computer Vision and Patten Recognition , , 2010a . . p.57 - - 64 . . . .
J.M. Alvarez , , , F. Lumbreras , , , T. Gevers , , , A.M. Lopez . . Geographic Information for Vision-Based Road Detection . . IEEE Intelligent Vehicles Symp. , , 2010b . . p.621 - - 626 . . . .
J.M. Alvarez , , , T. Gevers , , , Y. LeCun , , , A.M. Lopez . . Road Scene Segmentation from a Single Image . . European Conf. on Computer Vision , , 2012 . . p.376 - - 389 . . . .
J.M. Alvarez , , , T. Gevers , , , F. Diego , , , A.M. Lopez . . Road geometry classification by adaptive shape models . . IEEE Trans. Intell. Transp. Syst. , , 2013 . . 14 ( ( 1 ): ): 459 - - 468 . . DOI: 10.1109/TITS.2012.2221088 http://doi.org/10.1109/TITS.2012.2221088 . .
P. Bellutta , , , R. Manduchi , , , L. Matthies , , , K. Owens , , , A. Rankin . . Terrain Perception for DEMO Ⅲ . . Proc. IEEE Intelligent Vehicles Symp. , , 2000 . . p.326 - - 331 . . . .
M. Bertozzi , , , A. Broggi . . GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection . . IEEE Trans. Image Process. , , 1998 . . 7 ( ( 1 ): ): 62 - - 81 . . DOI: 10.1109/83.650851 http://doi.org/10.1109/83.650851 . .
Y. Boykov , , , O. Veksler , , , R. Zabih . . Fast approximate energy minimization via graph cuts . . IEEE Trans. Pattern Anal. Mach. Intell. , , 2001 . . 23 ( ( 11 ): ): 1222 - - 1239 . . DOI: 10.1109/34.969114 http://doi.org/10.1109/34.969114 . .
N. Dalal , , , B. Triggs . . Histogram of Oriented Gradient for Human Detection . . IEEE Computer Society Conf. on Computer Vision and Pattern Recognition , , 2005 . . p.886 - - 893 . . . .
K.B. Duan , , , S.S. Keerthi , , , W. Chu , , , A.K. Shevade , , , A.N. Poo . . Multi-category Classification by Soft-Max Combination of Binary Classifiers.4th Int . . Workshop on Multiple Classifier Systems , , 2003 . . p.125 - - 134 . . DOI: 10.1007/3-540-44938-8_13 http://doi.org/10.1007/3-540-44938-8_13 . .
P. Felzenszwalb , , , D. Huttenlocher . . Efficient graphbased image segmentation . . Int. J. Comput. Vis. , , 2004 . . 59 ( ( 2 ): ): 167 - - 181 . . DOI: 10.1023/B:VISI.0000022288.19776.77 http://doi.org/10.1023/B:VISI.0000022288.19776.77 . .
C.Z. Guo , , , S. Mita , , , D. McAllester . . MRF-Based Road Detection with Unsupervised Learning for Autonomous Driving in Changing Environments . . IEEE Intelligent Vehicles Symp. , , 2010 . . p.361 - - 368 . . . .
Y.H. He , , , H. Wang , , , B. Zhang . . Color based road detection in urban traffic scenes . . IEEE Trans. Intell. Transp. Syst. , , 2004 . . 5 ( ( 4 ): ): 309 - - 318 . . DOI: 10.1109/TITS.2004.838221 http://doi.org/10.1109/TITS.2004.838221 . .
D. Hoiem , , , A.A. Efros , , , M. Hebert . . Recovering surface layout from an image . . Int. J. Comput. Vis. , , 2007 . . 75 ( ( 1 ): ): 151 - - 172 . . DOI: 10.1007/s11263-006-0031-y http://doi.org/10.1007/s11263-006-0031-y . .
A. Kelly , , , A. Stentz , , , O. Amidi , , , M. Bode , , , D. Bradley , , , A. Diaz-Calderon , , , M. Happold , , , H. Herman , , , R. Mandelbaum , , , T. Pilarski , , , 等 . . Toward reliable off road autonomous vehicles operating in challenging environments . . Int. J. Robot. Res. , , 2006 . . 25 ( ( 5-6 ): ): 449 - - 483 . . DOI: 10.1177/0278364906065543 http://doi.org/10.1177/0278364906065543 . .
H. Kong , , , J.Y. Audibert , , , J. Ponce . . Vanishing Point Detection for Road Detection . . IEEE Conf. on Computer Vision and Pattern Recognition , , 2009 . . p.96 - - 103 . . . .
S. Lazebnik , , , C. Schmid , , , J. Ponce . . Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories . . IEEE Computer Society Conf. on Computer Vision and Pattern Recognition , , 2006 . . p.2169 - - 2178 . . . .
P. Lombardi , , , M. Zanin , , , S. Messelodi . . Switching Models for Vision-Based On-Board Road Detection . . IEEE Intelligent Vehicles Symp. , , 2005 . . p.67 - - 72 . . . .
A. Lookingbill , , , J. Rogers , , , D. Lieb , , , J. Curry , , , S. Thrun . . Reverse optical flow for self-supervised adaptive autonomous robot navigation . . Int. J. Comput. Vis. , , 2007 . . 74 ( ( 3 ): ): 287 - - 302 . . DOI: 10.1007/s11263-006-0024-x http://doi.org/10.1007/s11263-006-0024-x . .
M. Lutzeler , , , E.D. Dick . . Road Recognition with Marveye . . Proc. IEEE Intelligent-Vehicles Symp. , , 1998 . . p.341 - - 346 . . . .
P. Moghadam , , , J.A. Starzyk , , , W.S. Wijesoma . . Fast vanishing point detection in unstructured environments . . IEEE Trans. Image Process. , , 2012 . . 21 ( ( 1 ): ): 425 - - 430 . . DOI: 10.1109/TIP.2011.2162422 http://doi.org/10.1109/TIP.2011.2162422 . .
C. Thorpe , , , J. Carlson , , , D. Duggins . . Safe Robot Driving in Cluttered Environments . . 11th Int. Symp. of Robotics Research , , 2003 . . p.271 - - 280 . . . .
S. Thrun , , , M. Montemerlo , , , H. Dahlkamp , , , D. Stavens , , , A. Aron , , , J. Diebel , , , P. Fong , , , J. Gale , , , M. Halpenny , , , G. Hoffmann , , , 等 . . Stanley: the robot that won the DARPA grand challenge . . J. Field Robot. , , 2006 . . 23 ( ( 9 ): ): 661 - - 692 . . DOI: 10.1002/rob.20147 http://doi.org/10.1002/rob.20147 . .
K.E.A. van de Sande , , , T. Gevers , , , C.G.M. Snoek . . Evaluating color descriptors for object and scene recognition . . IEEE Trans. Pattern Anal. Mach. Intell. , , 2010 . . 32 ( ( 9 ): ): 1582 - - 1596 . . DOI: 10.1109/TPAMI.2009.154 http://doi.org/10.1109/TPAMI.2009.154 . .
Y. Wang , , , E.K. Teoh , , , D.G. Shen . . Lane detection and tracking using B-snake . . Image Vis. Comput. , , 2004 . . 22 ( ( 4 ): ): 269 - - 280 . . DOI: 10.1016/j.imavis.2003.10.003 http://doi.org/10.1016/j.imavis.2003.10.003 . .
Y. Wang , , , L. Bai , , , M. Fairhurst . . Robust road modeling and tracking using condensation . . IEEE Trans. Intell. Transp. Syst. , , 2008 . . 9 ( ( 4 ): ): 570 - - 579 . . DOI: 10.1109/TITS.2008.2006733 http://doi.org/10.1109/TITS.2008.2006733 . .
G. Zhang , , , N. Zheng , , , C. Cui , , , Y.Z. Yan , , , Z.J. Yuan . . An Efficient Road Detection Method in Noisy Urban Environment . . IEEE Intelligent Vehicles Symp. , , 2009 . . p.556 - - 561 . . . .
S.Y. Zhou , , , K. Iagnemma . . Self-Supervised Learning Method for Unstructured Road Detection Using Fuzzy Support Vector Machines . . IEEE/RSJ Int. Conf. on Intelligent Robots and Systems , , 2010 . . p.1183 - - 1189 . . . .
S.Y. Zhou , , , J.W. Gong , , , G.G. Xiong , , , H.Y. Chen , , , K. Iagnemma . . Road Detection Using Support Vector Machine Based on Online Learning and Evaluation . . IEEE Intelligent Vehicles Symp. , , 2010 . . p.256 - - 261 . . . .
- L-PDFDownload
- Meta-XMLDownload
- BibTeXDownload
- EndnoteDownload
- RefMan Download
- NoteExpressDownload
- NoteFirstDownload
Publicity Resources
Related Articles
Related Author
Related Institution
Chat- Address：Zhejiang University Press, 148 Tianmushan Road, Hangzhou, China Postal code：310028
- Tel：+86-571-88273162 Email：fitee@zju.edu.cn
- Copyright © 2000 - 2025, Zhejiang University Press 京ICP备09064830号-19
京公网安备11010802024621 - It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
- Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
