mSonar,
2011
WWW Link.
Vendor, Lane Following.
1106
Phone app to follow lanes using camera phone. Applied to navigation.
From Lustancia LTD.
Barnes, R.R.[Robert R.],
Myers, C.L.[Charles L.],
Driver alert system,
US_Patent4,348,652, Sep 7, 1982
WWW Link. Line detection using IR illumination.
BibRef
8209
Tsuchihashi, T.[Toshio],
Vehicle for driving along a lead line,
US_Patent4,588,041, May 13, 1986
WWW Link.
BibRef
8605
Yamamoto, K.[Kenzo],
Method and apparatus for controlling travel of an
automatic guided vehicle,
US_Patent4,593,239, Jun 3, 1986
WWW Link.
BibRef
8606
Swenson, R.R.[Ronald R.],
Floor position sensing apparatus and method,
US_Patent4,613,804, Sep 23, 1986
WWW Link. follow marked path
BibRef
8609
Barton, R.R.[Russell R.],
Vehicle tracking system,
US_Patent4,630,109, Dec 16, 1986
WWW Link. Follow distinct white stripe.
BibRef
8612
Kenue, S.K.,
LANELOK: Detection of Lane Boundaries and Vehicle
Tracking Using Image-Processing Techniques, Part I: Hough-Transform
Region-Tracing and Correlation Algorithms,
And:
Part II: Template Matching Algorithms,
GM ResearchTR, November 1989.
BibRef
8911
And:
Both are in:
SPIE(1195), November 1989.
Report on GM effort in road detection, find likely boundaries,
track through the frames.
BibRef
Kenue, S.K.,
Bajpayee, S.,
LaneLok: Robust Line and Curve Fitting of Lane Boundaries,
SPIE(1831), 1990, pp. 491-503. Boston.
BibRef
9000
Kenue, S.K.[Surender K.],
Vision method of detecting lane boundaries and obstacles,
US_Patent4,970,653, Nov 13, 1990
WWW Link.
BibRef
9011
And:
LANELOK: An Algorithm for Extending the Lane Sensing
Operating Range to 100 Feet,
SPIE(1388), November 1990.
BibRef
And:
GM ResearchLabs TR.
BibRef
Ogawa, H.[Hiroshi],
Miyazaki, Y.[Yasuyuki],
Yoshida, S.[Susumu],
Unmanned vehicle control system and method,
US_Patent4,665,487, May 12, 1987
WWW Link.
BibRef
8705
Ishikawa, S.,
Kuwamoto, H., and
Ozawa, S.,
Visual Navigation of an Autonomous Vehicle Using White Line
Recognition,
PAMI(10), No. 5, September 1988, pp. 743-749.
IEEE DOI Follow the white stripe. Simple processing, but with collision
avoidance. all visual control.
BibRef
8809
Ishikawa, S.,
Ozawa, S.,
A Method of Image Guided Vehicle Using White Line Recognition,
CVPR86(47-53).
White stripe following.
BibRef
8600
Mathur, B.P.[Bimal P.],
Wang, H.T.[H. Taichi],
Haendel, R.S.[Richard S.],
Vehicle lane position detection system,
US_Patent5,351,044, Sep 27, 1994
WWW Link.
BibRef
9409
Li, W.,
Lu, G.T.,
Wang, Y.Q.,
Recognizing White Line Markings for Vision-Guided
Vehicle Navigation by Fuzzy-Reasoning,
PRL(18), No. 8, August 1997, pp. 771-780.
9801
BibRef
Chen, K.H.,
Tsai, W.H.,
Vision-Based Autonomous Land Vehicle Guidance in Outdoor Road Environments
Using Combined Line and Road Following Techniques,
JRS(14), No. 10, October 1997, pp. 711-728.
9710
BibRef
Chen, G.Y.,
Tsai, W.H.,
An Incremental-Learning-by-Navigation Approach to Vision-Based
Autonomous Land Vehicle Guidance in Indoor Environments Using
Vertical Line Information and Multiweighted
Generalized Hough Transform Technique,
SMC-B(28), No. 5, October 1998, pp. 740-748.
IEEE Top Reference.
9810
BibRef
Guiducci, A.[Antonio],
Camera Calibration for Road Applications,
CVIU(79), No. 2, August 2000, pp. 250-266.
DOI Link
0008
BibRef
Guiducci, A.[Antonio],
Parametric Model of the Perspective Projection of a Road with
Applications to Lane Keeping and 3D Road Reconstruction,
CVIU(73), No. 3, March 1999, pp. 414-427.
DOI Link
BibRef
9903
Goldbeck, J.,
Huertgen, B.,
Ernst, S.,
Kelch, L.,
Lane following combining vision and DGPS,
IVC(18), No. 5, April 2000, pp. 425-433.
Elsevier DOI
0003
BibRef
Lai, A.H.S.,
Yung, N.H.C.,
Lane Detection by Orientation and Length Discrimination,
SMC-B(30), No. 4, August 2000, pp. 539-548.
IEEE Top Reference.
0008
BibRef
Wang, Y.[Yue],
Shen, D.G.[Ding-Gang],
Teoh, E.K.[Eam Khwang],
Lane detection using spline model,
PRL(21), No. 6-7, June 2000, pp. 677-689.
0006
BibRef
Wang, Y.[Yue],
Teoh, E.K.[Eam Khwang],
Shen, D.G.[Ding-Gang],
Lane detection and tracking using B-Snake,
IVC(22), No. 4, 1 April 2004, pp. 269-280.
Elsevier DOI
0402
BibRef
Wang, Y.,
Shen, D.,
Teoh, E.K.,
Wang, H.,
A Novel Lane Model for Lane Boundary Detection,
MVA98(xx-yy).
BibRef
9800
Beauvais, M.,
Lakshmanan, S.,
CLARK: a heterogeneous sensor fusion method for finding lanes and
obstacles,
IVC(18), No. 5, April 2000, pp. 397-413.
Elsevier DOI
0003
BibRef
Ma, B.[Bing],
Lakshmanan, S.[Sridhar],
Hero, III, A.O.[Alfred O.],
Simultaneous detection of lane and pavement boundaries using
model-based multisensor fusion,
ITS(1), No. 3, September 2000, pp. 135-147.
IEEE Abstract.
0402
BibRef
Earlier:
Road and lane Edge detection with Multisensor Fusion Methods,
ICIP99(II:686-690).
IEEE DOI
BibRef
Yasui, N.[Nobuhiko],
Iisaka, A.[Atsushi],
Kaneko, M.[Mamoru],
Local positioning apparatus, and a method therefor,
US_Patent6,091,833, Jul 18, 2000
WWW Link. Lane position.
BibRef
0007
Olivieri, M.[Massimiliano],
Fabbrizio, V.[Vito],
Guerrieri, R.[Roberto],
Kramer, A.[Alan],
Method for identifying marking stripes of road lanes,
US_Patent6,212,287, Apr 3, 2001
WWW Link.
BibRef
0104
Park, J.W.[Jong Woung],
Lee, J.W.[Joon Woong],
Jhang, K.Y.[Kyung Young],
A Lane-Curve Detection Based on an LCF,
PRL(24), No. 14, October 2003, pp. 2301-2313.
Elsevier DOI
0307
BibRef
Kang, D.J.[Dong-Joong],
Jung, M.H.[Mun-Ho],
Road lane segmentation using dynamic programming for active safety
vehicles,
PRL(24), No. 16, December 2003, pp. 3177-3185.
Elsevier DOI
0310
BibRef
Yim, Y.U.[Young Uk],
Oh, S.Y.[Se-Young],
Three-feature based automatic lane detection algorithm (TFALDA) for
autonomous driving,
ITS(4), No. 4, December 2003, pp. 219-225.
IEEE Abstract.
0402
BibRef
Li, Q.[Qing],
Zheng, N.N.[Nan-Ning],
Cheng, H.[Hong],
Springrobot:
A Prototype Autonomous Vehicle and its Algorithms for Lane Detection,
ITS(5), No. 4, December 2004, pp. 300-308.
IEEE Abstract.
0501
BibRef
Wang, J.,
Schroedl, S.,
Mezger, K.,
Ortloff, R.,
Joos, A.,
Passegger, T.,
Lane Keeping Based on Location Technology,
ITS(6), No. 3, September 2005, pp. 351-356.
IEEE DOI
0509
BibRef
Choi, S.Y.[Sung Yug],
Lee, J.M.[Jang Myung],
Applications of moving windows technique to autonomous vehicle
navigation,
IVC(24), No. 2, 1 February 2006, pp. 120-130.
Elsevier DOI
0604
Moving window; Lane detection; Obstacle detection; Mobile robot;
Corridor driving
BibRef
Cheng, H.Y.,
Jeng, B.S.,
Tseng, P.T.,
Fan, K.C.,
Lane Detection With Moving Vehicles in the Traffic Scenes,
ITS(7), No. 4, December 2006, pp. 571-582.
IEEE DOI
0701
BibRef
Zhang, Q.,
Couloigner, I.,
Accurate Centerline Detection and Line Width Estimation of Thick Lines
Using the Radon Transform,
IP(16), No. 2, February 2007, pp. 310-316.
IEEE DOI
0702
BibRef
Dao, T.S.,
Leung, K.Y.K.,
Clark, C.M.,
Huissoon, J.P.,
Markov-Based Lane Positioning Using Intervehicle Communication,
ITS(8), No. 4, December 2007, pp. 641-650.
IEEE DOI
0712
BibRef
Wu, S.J.,
Chiang, H.H.,
Perng, J.W.,
Chen, C.J.,
Wu, B.F.,
Lee, T.T.,
The Heterogeneous Systems Integration Design and Implementation for
Lane Keeping on a Vehicle,
ITS(9), No. 2, June 2008, pp. 246-263.
IEEE DOI
0806
BibRef
Chiang, H.H.[Hsin-Han],
Wu, S.J.[Shinq-Jen],
Perng, J.W.[Jau-Woei],
Wu, B.F.[Bing-Fei],
Lee, T.T.[Tsu-Tian],
The Human-in-the-Loop Design Approach to the Longitudinal Automation
System for an Intelligent Vehicle,
SMC-A(40), No. 4, July 2010, pp. 708-720.
IEEE DOI
1007
BibRef
Kim, Z.[Zu_Whan],
Robust Lane Detection and Tracking in Challenging Scenarios,
ITS(9), No. 1, March 2008, pp. 16-26.
IEEE DOI
0803
BibRef
Earlier:
Realtime Road Detection by Learning from One Example,
WACV05(I: 455-460).
IEEE DOI
0502
BibRef
Du, J.,
Barth, M.J.,
Next-Generation Automated Vehicle Location Systems:
Positioning at the Lane Level,
ITS(9), No. 1, March 2008, pp. 48-57.
IEEE DOI
0803
BibRef
Hassouna, M.S.[M. Sabry],
Abdel-Hakim, A.E.[Alaa E.],
Farag, A.A.[Aly A.],
PDE-Based Robust Robotic Navigation,
IVC(27), No. 1-2, January 2009, pp. 10-18.
Elsevier DOI
0804
BibRef
Earlier:
CRV05(176-183).
IEEE DOI
0505
BibRef
And:
Robust Robotic Path Planning Using Level Sets,
ICIP05(III: 473-476).
IEEE DOI
0512
See also Image content-based active sensor planning for a mobile trinocular active vision system. Robotic navigation; Level set methods; Fast marching methods; Path
planning; Optimum path; Skeletonization
BibRef
Farag, A.A.[Aly A.],
Abdel-Hakim, A.E.[Alaa E.],
Virtual Forces for Camera Planning in Smart Vision Systems,
WACV05(I: 269-274).
IEEE DOI
0502
BibRef
Hassouna, M.S.[M. Sabry],
Farag, A.A.[Aly A.],
Robust Centerline Extraction Framework Using Level Sets,
CVPR05(I: 458-465).
IEEE DOI
0507
BibRef
Toledo-Moreo, R.,
Zamora-Izquierdo, M.A.,
IMM-Based Lane-Change Prediction in Highways With Low-Cost GPS/INS,
ITS(10), No. 1, March 2009, pp. 180-185.
IEEE DOI
0903
BibRef
Danescu, R.G.,
Nedevschi, S.,
Probabilistic Lane Tracking in Difficult Road Scenarios Using
Stereovision,
ITS(10), No. 2, June 2009, pp. 272-282.
IEEE DOI
0906
BibRef
Cheng, H.Y.,
Yu, C.C.,
Tseng, C.C.,
Fan, K.C.,
Hwang, J.N.,
Jeng, B.S.,
Environment classification and hierarchical lane detection for
structured and unstructured roads,
IET-CV(4), No. 1, March 2010, pp. 37-49.
DOI Link
1001
BibRef
Jiang, R.[Ruyi],
Klette, R.[Reinhard],
Vaudrey, T.[Tobi],
Wang, S.G.[Shi-Gang],
Lane detection and tracking using a new lane model and distance
transform,
MVA(22), No. 4, July 2011, pp. 721-737.
WWW Link.
1107
BibRef
Earlier:
New Lane Model and Distance Transform for Lane Detection and Tracking,
CAIP09(1044-1052).
Springer DOI
0909
BibRef
Xiao, J.S.[Jin-Sheng],
Luo, L.[Li],
Yao, Y.[Yuan],
Zou, W.[Wentao],
Klette, R.[Reinhard],
Lane Detection Based on Road Module and Extended Kalman Filter,
PSIVT17(382-395).
Springer DOI
1802
BibRef
Amditis, A.,
Bimpas, M.,
Thomaidis, G.,
Tsogas, M.,
Netto, M.,
Mammar, S.,
Beutner, A.,
Mohler, N.,
Wirthgen, T.,
Zipser, S.,
Etemad, A.,
da Lio, M.,
Cicilloni, R.,
A Situation-Adaptive Lane-Keeping Support System:
Overview of the SAFELANE Approach,
ITS(11), No. 3, September 2010, pp. 617-629.
IEEE DOI
1003
BibRef
Nieto, M.[Marcos],
Arróspide Laborda, J.[Jon],
Salgado, L.[Luis],
Road environment modeling using robust perspective analysis and
recursive Bayesian segmentation,
MVA(22), No. 6, November 2011, pp. 927-945.
WWW Link.
1110
BibRef
Nieto, M.[Marcos],
Salgado, L.[Luis],
Jaureguizar, F.[Fernando],
Arróspide Laborda, J.[Jon],
Robust multiple lane road modeling based on perspective analysis,
ICIP08(2396-2399).
IEEE DOI
0810
BibRef
Kheyrollahi, A.[Alireza],
Breckon, T.P.[Toby P.],
Automatic real-time road marking recognition using a feature driven
approach,
MVA(23), No. 1, January 2012, pp. 123-133.
WWW Link.
1201
BibRef
Kim, J.Y.[Ju-Young],
Jang, J.S.[Ja-Soon],
A simple model for a lane detection system,
SPIE(Newsroom), February 15, 2012.
DOI Link
1202
An efficient algorithm for detecting lane markers uses the log-polar
transform and random sample consensus to achieve robust performance
under various road conditions.
BibRef
Kim, J.Y.,
Lim, H.R.,
Lee, C.S.,
Jang, J.S.,
An efficient lane markers detection algorithm using
log-polar transform and RANSAC,
SPIE(8135), 2011, pp. 81351J.
DOI Link
BibRef
1100
Gikas, V.,
Stratakos, J.,
A Novel Geodetic Engineering Method for Accurate and Automated
Road/Railway Centerline Geometry Extraction Based on the Bearing
Diagram and Fractal Behavior,
ITS(13), No. 1, March 2012, pp. 115-126.
IEEE DOI
1203
BibRef
Borkar, A.,
Hayes, M.,
Smith, M.T.,
A Novel Lane Detection System With Efficient Ground Truth Generation,
ITS(13), No. 1, March 2012, pp. 365-374.
IEEE DOI
1203
BibRef
Cameron, M.[Mark],
Al-Bahadly, I.[Ibrahim],
Zakaria, Z.[Zulkarnay],
Ayob, N.M.N.[Nor Muzakkir Nor],
A Line Detection Algorithm for Road Remarking,
Sensors(140), No. 5, May 2012, pp. 65-73.
HTML Version.
BibRef
1205
Wu, C.F.,
Lin, C.J.,
Lee, C.Y.,
Applying a Functional Neurofuzzy Network to Real-Time Lane Detection
and Front-Vehicle Distance Measurement,
SMC-C(42), No. 4, July 2012, pp. 577-589.
IEEE DOI
1206
BibRef
Fang, Y.F.[Yun-Fei],
Chu, F.[Feng],
Mammar, S.,
Zhou, M.[MengChu],
Optimal Lane Reservation in Transportation Network,
ITS(13), No. 2, June 2012, pp. 482-491.
IEEE DOI
1206
Not land detection.
BibRef
Vu, A.[Anh],
Ramanandan, A.,
Chen, A.[Anning],
Farrell, J.A.,
Barth, M.,
Real-Time Computer Vision/DGPS-Aided Inertial Navigation System for
Lane-Level Vehicle Navigation,
ITS(13), No. 2, June 2012, pp. 899-913.
IEEE DOI
1206
BibRef
Demcenko, A.,
Tamosiunaite, M.,
Vidugiriene, A.,
Jakevicius, L.,
Estimation of Lane Marker Parameters With High Correlation to Steering
Signal,
ITS(13), No. 2, June 2012, pp. 962-967.
IEEE DOI
1206
BibRef
Gopalan, R.,
Hong, T.,
Shneier, M.,
Chellappa, R.,
A Learning Approach Towards Detection and Tracking of Lane Markings,
ITS(13), No. 3, September 2012, pp. 1088-1098.
IEEE DOI
1209
BibRef
Alam, N.,
Balaei, A.T.,
Dempster, A.G.,
An Instantaneous Lane-Level Positioning Using DSRC Carrier Frequency
Offset,
ITS(13), No. 4, December 2012, pp. 1566-1575.
IEEE DOI
1212
BibRef
Liu, G.,
Worgotter, F.,
Markelic, I.,
Stochastic Lane Shape Estimation Using Local Image Descriptors,
ITS(14), No. 1, March 2013, pp. 13-21.
IEEE DOI
1303
BibRef
Sivaraman, S.,
Trivedi, M.M.,
Integrated Lane and Vehicle Detection, Localization, and Tracking:
A Synergistic Approach,
ITS(14), No. 2, 2013, pp. 906-917.
IEEE DOI
1307
Image edge detection; Kalman filters; driver assistance;
lane departure
See also Vehicle Detection by Independent Parts for Urban Driver Assistance.
BibRef
Sivaraman, S.[Sayanan],
Trivedi, M.M.[Mohan M.],
Dynamic Probabilistic Drivability Maps for Lane Change and Merge
Driver Assistance,
ITS(15), No. 5, October 2014, pp. 2063-2073.
IEEE DOI
1410
data structures
BibRef
Satzoda, R.K.,
Trivedi, M.M.,
Drive Analysis Using Vehicle Dynamics and Vision-Based Lane Semantics,
ITS(16), No. 1, February 2015, pp. 9-18.
IEEE DOI
1502
Computer crashes
BibRef
Satzoda, R.K.[Ravi Kumar],
Trivedi, M.M.[Mohan M.],
On Enhancing Lane Estimation Using Contextual Cues,
CirSysVideo(25), No. 11, November 2015, pp. 1870-1881.
IEEE DOI
1511
BibRef
Earlier:
On Performance Evaluation Metrics for Lane Estimation,
ICPR14(2625-2630)
IEEE DOI
1412
BibRef
And:
Efficient Lane and Vehicle Detection with Integrated Synergies
(ELVIS),
ECVW14(708-713)
IEEE DOI
1409
BibRef
Earlier:
Vision-Based Lane Analysis:
Exploration of Issues and Approaches for Embedded Realization,
ECVW13(604-609)
IEEE DOI
1309
Accuracy.
embedded system; intelligent driver assistance systems; lane detection.
computational efficiency
BibRef
Sivaraman, S.[Sayanan],
Morris, B.T.[Brendan T.],
Trivedi, M.M.[Mohan M.],
Learning multi-lane trajectories using vehicle-based vision,
CVVT11(2070-2076).
IEEE DOI
1201
The other cars.
BibRef
McCall, J.C.,
Trivedi, M.M.,
An integrated, robust approach to lane marking detection and lane
tracking,
IVS04(533-537).
IEEE DOI
0411
BibRef
Li, X.Y.[Xiang-Yang],
Fang, X.Z.[Xiang-Zhong],
Parallel-Snake with Balloon Force for Lane Detection,
IEICE(E97-D), No. 2, February 2013, pp. 349-352.
WWW Link.
1402
BibRef
Wu, P.C.[Pei-Chen],
Chang, C.Y.[Chin-Yu],
Lin, C.H.[Chang Hong],
Lane-mark extraction for automobiles under complex conditions,
PR(47), No. 8, 2014, pp. 2756-2767.
Elsevier DOI
1405
Line fitting
BibRef
Shin, B.S.[Bok-Suk],
Xu, Z.Z.[Ze-Zhong],
Klette, R.[Reinhard],
Visual lane analysis and higher-order tasks: a concise review,
MVA(25), No. 6, 2014, pp. 1519-1547.
WWW Link.
1408
BibRef
Shin, B.S.[Bok-Suk],
Tao, J.L.[Jun-Li],
Klette, R.[Reinhard],
A superparticle filter for lane detection,
PR(48), No. 11, 2015, pp. 3333-3345.
Elsevier DOI
1506
BibRef
Earlier: A2, A1, A3:
Wrong Roadway Detection for Multi-lane Roads,
CAIP13(II:50-58).
Springer DOI
1311
Lane model
BibRef
Mathibela, B.,
Newman, P.,
Posner, I.,
Reading the Road: Road Marking Classification and Interpretation,
ITS(16), No. 4, August 2015, pp. 2072-2081.
IEEE DOI
1508
Feature extraction
BibRef
de Paula, M.B.,
Jung, C.R.,
Automatic Detection and Classification of Road Lane Markings Using
Onboard Vehicular Cameras,
ITS(16), No. 6, December 2015, pp. 3160-3169.
IEEE DOI
1512
Bayes methods
BibRef
Jung, S.,
Youn, J.,
Sull, S.,
Efficient Lane Detection Based on Spatiotemporal Images,
ITS(17), No. 1, January 2016, pp. 289-295.
IEEE DOI
1601
Image edge detection
BibRef
Nieto, M.[Marcos],
Cortés, A.[Andoni],
Otaegui, O.[Oihana],
Arróspide, J.[Jon],
Salgado, L.[Luis],
Real-time lane tracking using Rao-Blackwellized particle filter,
RealTimeIP(11), No. 1, January 2016, pp. 179-191.
Springer DOI
1601
BibRef
Du, X.X.[Xin-Xin],
Tan, K.K.[Kok Kiong],
Vision-based approach towards lane line detection and vehicle
localization,
MVA(27), No. 2, February 2016, pp. 175-191.
WWW Link.
1602
BibRef
Cui, D.,
Xue, J.,
Zheng, N.,
Real-Time Global Localization of Robotic Cars in Lane Level via Lane
Marking Detection and Shape Registration,
ITS(17), No. 4, April 2016, pp. 1039-1050.
IEEE DOI
1604
Accuracy
BibRef
Du, X.,
Tan, K.K.,
Comprehensive and Practical Vision System for Self-Driving Vehicle
Lane-Level Localization,
IP(25), No. 5, May 2016, pp. 2075-2088.
IEEE DOI
1604
image motion analysis
BibRef
Niu, J.W.[Jian-Wei],
Lu, J.[Jie],
Xu, M.L.[Ming-Liang],
Lv, P.[Pei],
Zhao, X.[Xiaoke],
Robust Lane Detection using Two-stage Feature Extraction with Curve
Fitting,
PR(59), No. 1, 2016, pp. 225-233.
Elsevier DOI
1609
Lane detection
BibRef
Das, A.,
Srinivasa Murthy, S.,
Suddamalla, U.,
Enhanced Algorithm of Automated Ground Truth Generation and
Validation for Lane Detection System by M^2 BMT,
ITS(18), No. 4, April 2017, pp. 996-1005.
IEEE DOI
1704
modified min-between-max thresholding
BibRef
Cheng, G.,
Wang, Y.,
Xu, S.,
Wang, H.,
Xiang, S.,
Pan, C.,
Automatic Road Detection and Centerline Extraction via Cascaded
End-to-End Convolutional Neural Network,
GeoRS(55), No. 6, June 2017, pp. 3322-3337.
IEEE DOI
1706
Automobiles, Data mining, Feature extraction, Image segmentation,
Neural networks, Remote sensing, Roads,
Cascaded convolutional neural network (CasNet), end-to-end,
road centerline extraction, road, detection
BibRef
Piao, J.C.[Jing-Chun],
Shin, H.C.[Hyun-Chul],
Robust hypothesis generation method using binary blob analysis for
multi-lane detection,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1210-1218.
DOI Link
1712
BibRef
Yoo, J.H.,
Lee, S.W.,
Park, S.K.,
Kim, D.H.,
A Robust Lane Detection Method Based on Vanishing Point Estimation
Using the Relevance of Line Segments,
ITS(18), No. 12, December 2017, pp. 3254-3266.
IEEE DOI
1712
Estimation, Feature extraction, Image color analysis,
Image segmentation, Probabilistic logic, Roads, Robustness,
vanishing point estimation
BibRef
Vivacqua, R.P.D.,
Bertozzi, M.,
Cerri, P.,
Martins, F.N.,
Vassallo, R.F.,
Self-Localization Based on Visual Lane Marking Maps: An Accurate
Low-Cost Approach for Autonomous Driving,
ITS(19), No. 2, February 2018, pp. 582-597.
IEEE DOI
1802
Cameras, Laser radar, Roads, Robustness, Sensors, Visualization,
Autonomous driving, computer vision, dead reckoning,
mapping and localization
BibRef
Bailo, O.,
Lee, S.,
Rameau, F.,
Yoon, J.S.,
Kweon, I.S.,
Robust Road Marking Detection and Recognition Using Density-Based
Grouping and Machine Learning Techniques,
WACV17(760-768)
IEEE DOI
1609
Cameras, Feature extraction, Image edge detection, Lighting,
Neural networks, Roads, Robustness
BibRef
Parajuli, A.[Avishek],
Celenk, M.[Mehmet],
Riley, H.B.[H. Bryan],
Performance Assessment of Predictive Lane Boundary Detection for
Non-uniformly Illuminated Roadway Driving Assistance,
CRV16(170-177)
IEEE DOI
1612
Driving Assistance Roadway Features
BibRef
Kim, H.S.[Hee-Soo],
Beak, S.H.[Seung-Hae],
Park, S.Y.[Soon-Yong],
Parallel Hough Space Image Generation Method for Real-Time Lane
Detection,
ACIVS16(81-91).
Springer DOI
1611
BibRef
Takahashi, G.,
Takeda, H.,
Nakamura, K.,
Drawing for Traffic Marking Using Bidirectional Gradient-based
Detection with MMS Lidar Intensity,
ISPRS16(B5: 725-732).
DOI Link
1610
BibRef
John, V.[Vijay],
Liu, Z.[Zheng],
Guo, C.[Chunzhao],
Mita, S.[Seiichi],
Kidono, K.[Kiyosumi],
Real-Time Lane Estimation Using Deep Features and Extra Trees
Regression,
PSIVT15(721-733).
Springer DOI
1602
BibRef
Saussard, R.[Romain],
Bouzid, B.[Boubker],
Vasiliu, M.[Marius],
Reynaud, R.[Roger],
The embeddability of lane detection algorithms on heterogeneous
architectures,
ICIP15(4694-4697)
IEEE DOI
1512
ADAS; Embedded Processing; Lane Detection
BibRef
Chen, T.[Tao],
Lu, S.[Shijian],
Context-aware lane marking detection on urban roads,
ICIP15(2557-2561)
IEEE DOI
1512
Lane marking; MSER; context-aware features; detection
BibRef
Teng, S.Y.[Shan-Yun],
Chuang, K.T.[Kun-Ta],
Huang, C.R.[Chun-Rong],
Li, C.C.[Cheng-Chun],
Lane detection in surveillance videos using vector-based hierarchy
clustering and density verification,
MVA15(345-348)
IEEE DOI
1507
Global Positioning System
BibRef
Chen, Y.C.[Yu-Chun],
Su, T.F.[Te-Feng],
Lai, S.H.[Shang-Hong],
Integrated Vehicle and Lane Detection with Distance Estimation,
IMEV14(473-485).
Springer DOI
1504
BibRef
Li, C.[Cheng],
Creusen, I.[Ivo],
Hazelhoff, L.[Lykele],
de With, P.H.N.[Peter H. N.],
Detection and Recognition of Road Markings in Panoramic Images,
IVVT14(448-458).
Springer DOI
1504
BibRef
Mazurek, P.[Przemyslaw],
Directional Filter and the Viterbi Algorithm for Line Following Robots,
ICCVG14(428-435).
Springer DOI
1410
BibRef
Aly, M.,
Real time detection of lane markers in urban streets,
IVS08(7-12).
IEEE DOI
BibRef
0800
Truong, Q.B.[Quoc Bao],
Lee, B.R.[Byung Ryong],
Heo, N.G.[Nam Geon],
Yum, Y.J.[Young Jim],
Kim, J.G.[Jong Gook],
Lane boundaries detection algorithm using vector lane concept,
ICARCV08(2319-2325).
IEEE DOI
1109
BibRef
Benmansour, N.,
Labayrade, R.,
Aubert, D.,
Glaser, S.,
Gruyer, D.,
A model driven 3D lane detection system using stereovision,
ICARCV08(1277-1282).
IEEE DOI
1109
BibRef
Liu, X.[Xin],
Dai, B.[Bin],
Song, J.Z.[Jin-Ze],
He, H.[Hangen],
Zhang, B.[Bo],
Real-Time Long-Range Lane Detection and Tracking for Intelligent
Vehicle,
ICIG11(654-659).
IEEE DOI
1109
See also Visual Saliency Based on Scale-Space Analysis in the Frequency Domain.
BibRef
An, X.J.[Xiang-Jing],
Li, J.[Jian],
Shang, E.[Erke],
He, H.[Hangen],
Multi-scale and Multi-orientation Local Feature Extraction for Lane
Detection Using High-Level Information,
ICIG11(576-581).
IEEE DOI
1109
BibRef
Li, J.[Jian],
An, X.J.[Xiang-Jing],
He, H.[Hangen],
Lane Detection Based on Visual Attention,
ICIG11(570-575).
IEEE DOI
1109
BibRef
Shang, E.[Erke],
Li, J.[Jian],
An, X.J.[Xiang-Jing],
He, H.[Hangen],
Lane Detection Using Steerable Filters and FPGA-based Implementation,
ICIG11(908-913).
IEEE DOI
1109
BibRef
Ben Romdhane, N.[Nadra],
Hammami, M.[Mohamed],
Ben-Abdallah, H.[Hanene],
A Comparative Study of Vision-Based Lane Detection Methods,
ACIVS11(46-57).
Springer DOI
1108
See also Comparative Study of Vision-Based Traffic Signs Recognition Methods, A.
BibRef
Ammar, M.[Moez],
Le Hégarat-Mascle, S.[Sylvie],
Mounier, H.[Hugues],
Road Surface Marking Classification Based on a Hierarchical Markov
Model,
ICIAR11(II: 348-359).
Springer DOI
1106
See also A-contrario Approach for Obstacle Detection in Assistance Driving Systems, An.
BibRef
Hara, T.[Takayuki],
Aoki, Y.[Yoshimitsu],
A robust road marking detection method with pseudo-top-view images for
creating database,
FCV11(1-5).
IEEE DOI
1102
BibRef
Wong, D.,
Deguchi, D.[Daisuke],
Ide, I.[Ichiro],
Murase, H.[Hiroshi],
Position Interpolation Using Feature Point Scale for Decimeter Visual
Localization,
CVRoads15(90-97)
IEEE DOI
1602
Cameras
BibRef
Noda, M.[Masafumi],
Takahashi, T.[Tomokazu],
Deguchi, D.[Daisuke],
Ide, I.[Ichiro],
Murase, H.[Hiroshi],
Kojima, Y.[Yoshiko],
Naito, T.[Takashi],
Vehicle Ego-Localization by Matching In-Vehicle Camera Images to an
Aerial Image,
CVVT10(163-173).
Springer DOI
1109
BibRef
Earlier:
Recognition of Road Markings from In-Vehicle Camera Images by a
Generative Learning Method,
MVA09(514-).
PDF File.
0905
BibRef
Cheng, G.,
Qian, Y.,
Elder, J.H.[James H.],
Fusing Geometry and Appearance for Road Segmentation,
CVRoads17(166-173)
IEEE DOI
1802
Adaptation models, Computational modeling, Dictionaries,
Image segmentation, Meteorology, Roads, Training
BibRef
Corral, E.[Eduardo],
Elder, J.H.[James H.],
Probabilistic Detection and Grouping of Highway Lane Marks,
CGC10(311).
PDF File.
1006
BibRef
Jiang, Y.[Yan],
Gao, F.[Feng],
Xu, G.[Guoyan],
Computer vision-based multiple-lane detection on straight road and in a
curve,
IASP10(114-117).
IEEE DOI
1004
BibRef
Borkar, A.[Amol],
Hayes, M.[Monson],
Smith, M.T.[Mark T.],
A Template Matching and Ellipse Modeling Approach to Detecting Lane
Markers,
ACIVS10(II: 179-190).
Springer DOI
1012
BibRef
Earlier:
Robust lane detection and tracking with ransac and Kalman filter,
ICIP09(3261-3264).
IEEE DOI
0911
BibRef
And:
Lane Detection and Tracking Using a Layered Approach,
ACIVS09(474-484).
Springer DOI
0909
BibRef
Shi, X.J.[Xue-Jie],
Kong, B.[Bin],
Zheng, F.[Fei],
A New Lane Detection Method Based on Feature Pattern,
CISP09(1-5).
IEEE DOI
0910
BibRef
Gao, T.[Tianshi],
Aghajan, H.[Hamid],
Self lane assignment using egocentric smart mobile camera for
intelligent GPS navigation,
Egocentric09(57-62).
IEEE DOI
0906
BibRef
Su, C.Y.[Chung-Yen],
Fan, G.H.[Gen-Hau],
An Effective and Fast Lane Detection Algorithm,
ISVC08(II: 942-948).
Springer DOI
0812
BibRef
Kang, Y.[Yousun],
Yamaguchi, K.[Koichiro],
Naito, T.[Takashi],
Ninomiya, Y.[Yoshiki],
Road Image Segmentation and Recognition Using Hierarchical
Bag-of-Textons Method,
PSIVT11(I: 248-256).
Springer DOI
1111
See also Feature Interaction Descriptor for Pedestrian Detection.
BibRef
Yamaguchi, K.[Koichiro],
Watanabe, A.[Akihiro],
Naito, T.[Takashi],
Ninomiya, Y.[Yoshiki],
Road region estimation using a sequence of monocular images,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Asai, T.[Toshihiro],
Yamaguchi, K.[Koichiro],
Kojima, Y.[Yoshiko],
Naito, T.[Takashi],
Ninomiya, Y.[Yoshiki],
3D Line Reconstruction of a Road Environment Using an In-Vehicle Camera,
ISVC08(II: 897-904).
Springer DOI
0812
BibRef
Lipski, C.[Christian],
Scholz, B.[Bjorn],
Berger, K.[Kai],
Linz, C.[Christian],
Stich, T.[Timo],
Magnor, M.[Marcus],
A Fast and Robust Approach to Lane Marking Detection and Lane Tracking,
Southwest08(57-60).
IEEE DOI
0803
BibRef
López, A.M.[Antonio M.],
Serrat, J.[Joan],
Cañero, C.[Cristina],
Lumbreras, F.[Felipe],
Robust Lane Lines Detection and Quantitative Assessment,
IbPRIA07(I: 274-281).
Springer DOI
0706
BibRef
Labayrade, R.,
How Autonomous Mapping Can Help a Road Lane Detection System ?,
ICARCV06(1-6).
IEEE DOI
0612
BibRef
Samadzadegan, F.,
Sarafraz, A.,
Tabibi, M.,
Automatic lane detection in image sequences for vision based navigation
purposes,
IEVM06(xx-yy).
PDF File.
0609
BibRef
Roncella, R.,
Forlani, G.[Gianfranco],
Automatic lane parameters extraction in mobile mapping sequences,
IEVM06(xx-yy).
PDF File.
0609
BibRef
Dupuis, J.,
Parizeau, M.,
Evolving a Vision-Based Line-Following Robot Controller,
CRV06(75-75).
IEEE DOI
0607
BibRef
Nourine, R.,
Boudihir, M.E.[M. Elarbi],
Khelifi, S.F.,
Application of Radon Transform to Lane Boundaries Tracking,
ICIAR04(II: 563-571).
Springer DOI
0409
BibRef
Cramer, H.,
Scheunert, U.,
Wanielik, G.,
A new approach for tracking lanes by fusing image measurements with map
data,
IVS04(607-612).
IEEE DOI
0411
BibRef
Dal Poz, A.P.[Aluir Porfírio],
Oliveira da Silva, M.A.[Marco Aurélio],
Active Testing and Edge Analysis for Road Centreline Extraction,
PCV02(B: 44).
0305
BibRef
Toth, C.K.[Charles K.],
Grejner-Brzezinska, D.A.[Dorota A.],
Near Real-Time Road Centerline Extraction,
PCV02(A: 362).
0305
BibRef
Muck, K.,
Nagel, H.H.,
Middendorf, M.,
Data-Driven Extraction of Curved Intersection Lanemarks from Road
Traffic Image Sequences,
ECCV00(II: 411-427).
Springer DOI
0003
BibRef
Behringer, R.,
Hötzl, S.,
Simultaneous Estimation of Pitch Angle and Lane Width
from the Video Image of a Marked Road,
IROS94(xx).
BibRef
9400
Kreucher, C.,
Lakshmanan, S.,
A Frequency Domain Approach to Lane Detection in Roadway Images,
ICIP99(II:31-35).
IEEE DOI
BibRef
9900
Descombes, X.,
Stoica, R.,
Zerubia, J.,
Two Markov point processes for simulating line networks,
ICIP99(II:36-40).
IEEE DOI Applied to Roads.
BibRef
9900
Yu, B., and
Jain, A.K.,
Lane Boundary Detection Using a Multiresolution Hough Transform,
ICIP97(II: 748-751).
IEEE DOI
BibRef
9700
Diebolt, F.[Frank],
Road Markings Recognition,
ICIP96(II: 669-672).
IEEE DOI
BibRef
9600
Inglebert, C.,
Road Line Tracking: An Approach Based On Spatio-Temporal Surface,
ICPR92(I:224-227).
IEEE DOI
BibRef
9200
Campbell, N.W.,
Thomas, B.T.,
Lane Boundary Tracking for an Autonomous Road Vehicle,
BMVC92(xx-yy).
PDF File.
9209
BibRef
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Indoor Navigation Issues, Lines, Walls, Doors, Flat Surfaces .