24.1.5 Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments

Chapter Contents (Back)
Remote Sensing. Road Detection. Recognize Roads. Line Detection. Aerial Image Analysis. Generally, given a starting point, follow the road. Some of this also is used in linking sections in other systems.
See also Road Junctions, Road Intersections.

Fischler, M.A., Tenenbaum, J.M., and Wolf, H.C.,
Detection of Roads and Linear Structures in Low Resolution Aerial Images Using Multi-Source Knowledge Integration Techniques,
CGIP(15), No. 3, March 1981, pp. 201-223. Reprinted:
Elsevier DOI RCV(741-752). BibRef 8103
Earlier: DARPAN79(87-100). Application, Cartography. The F* algorithm. Several edge/road detection techniques are applied to detect and then trace roads in images. BibRef

Fischler, M.A., Agin, G.J., Barrow, H.G., Bolles, R.C., Quam, L.H., Tenenbaum, J.M., and Wolf, H.C.,
The SRI Road Expert: An Overview,
DARPAN78(13-19). The early version of the road papers. BibRef 7800

Fischler, M.A.[Martin A.], Heller, A.J.[Aaron J.],
Automated Techniques for road Network Modeling,
DARPA98(501-516). Some interaction, 10 times speedup over manual. Find road feature points, link together, analyze, then edit BibRef 9800

Fischler, M.A.[Martin A.], Bolles, R.C.[Robert C.],
Evaluation of a Road-Centerline Data Model,
DARPA98(493-498). Evaluation BibRef 9800

Agin, G.J.,
Knowledge-Based Detection and Classification of Vehicles and Other Objects in Aerial Road Images,
DARPA79(66-71). Detect cars given the road. BibRef 7900

Quam, L.H.,
Road Tracking and Anomaly Detection in Aerial Imagery,
DARPA78(51-55). Road following paper. BibRef 7800


See also Building and Road Extraction from Aerial Photographs.

Vasudevan, S., Cannon, R.L., Bezdek, J.C., and Cameron, W.L.,
Heuristics for Intermediate-Level Road Finding Algorithms,
CVGIP(44), No. 2, November 1988, pp. 175-190.
Elsevier DOI Connecting road fragments based on road-like features. BibRef 8811

Fulford, M.C.[Martin C.],
The FASTRAK Automatic Digitising System,
PR(14), No. 1-6, 1981, pp. 65-74.
Elsevier DOI BibRef 8100

Zlotnick, A., and Carnine, Jr., P.D.,
Finding Road Seeds in Aerial Images,
CVGIP(57), No. 2, March 1993, pp. 243-260.
DOI Link Uses antiparallel pairs to generate road hypotheses followed by linking. Extends technique of
See also Cooperative Methods for Road Tracking in Aerial Imagery. by finding start points. BibRef 9303

Barzohar, M., Cooper, D.B.,
Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation,
PAMI(18), No. 7, July 1996, pp. 707-721.
IEEE DOI 9608
BibRef
Earlier: CVPR93(459-464).
IEEE DOI BibRef
And: DARPA93(465-469). BibRef
And:
Completely Automatic Reliable Finding of Main Roads in Aerial Images by Using Bayesian Methods,
BrownLEMS-118, March 1993. BibRef

Barzohar, M., Keren, D., Cooper, D.B.,
Recognizing Groups of Curves Based on New Affine Mutual Geometric Invariants, with Applications to Recognizing Intersecting Roads in Aerial Images,
ICPR94(A:205-209).
IEEE DOI BibRef 9400

Barzohar, M., and Cooper, D.B.,
New Geometric Stochastic Technology for Finding and Recognizing Roads and Their Features in Aerial Images,
Ascona95(255-264). BibRef 9500

Barzohar, M.[Meir], Cohen, M.[Moshe], Ziskind, I.[Ilan], and Cooper, D.B.,
Fast Robust Tracking of Curvy Partially Occluded Roads in Clutter in Aerial Images,
Ascona97(277-286). High Resolution, rural roads. Begin with seeds, track and merge the results. Does not smooth the boundaries. BibRef 9700

Barzohar, M., Cohen, M., Ziskind, I., and Cooper, D.B.,
Automatic and Robust Aerial Road Detection Based on Multihypothesis Generalized Kalman Filter Using Fully and Partially Occluded Models,
ICIP97(III: 134-137).
IEEE DOI 9710
BibRef

Geman, D., Jedynak, B.,
An Active Testing Model for Tracking Roads in Satellite Images,
PAMI(18), No. 1, January 1996, pp. 1-14.
IEEE DOI BibRef 9601
Earlier: UMassTech Report, August 1994. Track highways in SPOT imagery over large distances. Very good results. BibRef

Jedynak, B., and Roze, J.P.,
Tracking Roads in Satellite Images by Playing Twenty Questions,
Ascona95(243-253). Apply a set of tests (matched filters) one at a time to remove uncertainity about the road position. BibRef 9500

Netanyahu, N.S.[Nathan S.], Philomin, V.[Vasanth], Rosenfeld, A.[Azriel], Stromberg, A.J.[Arnold J.],
Robust Detection of Straight and Circular Road Segments in Noisy Aerial Images,
PR(30), No. 10, October 1997, pp. 1673-1686.
Elsevier DOI 9712
BibRef

Netanyahu, N.S.[Nathan S.], Philomin, V.[Vasanth], Stromberg, A.J.[Arnold J.], Netanyahu, N.S., Philomin, V., Stromberg, A.J.,
Robust Detection of Road Segments in Noisy Aerial Images,
ICPR96(II: 151-155).
IEEE DOI 9608
BibRef
And: UMDTR-3631, April 1996.
WWW Link. (Univ. of Maryland, USA) BibRef

Merlet, N., Zerubia, J.B.,
New Prospects in Line Detection by Dynamic-Programming,
PAMI(18), No. 4, April 1996, pp. 426-431.
IEEE DOI 9605
BibRef
Earlier:
New Prospects in Line Detection for Remote Sensing Images,
ICASSP94(xx). BibRef
Earlier:
Classical Mechanics and Road Detection in SPOT Images,
INRIAReport 1889, 1993. Dynamic Programming. Low resolution road detection. Connect broken roads. BibRef

Rochery, M.[Marie], Jermyn, I.H.[Ian H.], Zerubia, J.B.[Josiane B.],
Higher Order Active Contours,
IJCV(69), No. 1, August 2006, pp. 27-42.
Springer DOI 0606
Active Contours. BibRef
Earlier: INRIARR-5656, 2005.
HTML Version. BibRef
Earlier:
Phase Field Models and Higher-Order Active Contours,
ICCV05(II: 970-976).
IEEE DOI 0510
BibRef
New Higher-Order Active Contour Energies for Network Extraction,
ICIP05(II: 822-825).
IEEE DOI 0512
Arbitrary polynomial functionals, optimize with a level set approach. Prior energy term to describe network for roads. Special case of the model applied to road network extraction. BibRef

El Ghoul, A.[Aymen], Jermyn, I.H.[Ian H.], Zerubia, J.B.[Josiane B.],
A Theoretical and Numerical Study of a Phase Field Higher-Order Active Contour Model of Directed Networks,
ACCV10(II: 647-659).
Springer DOI 1011
BibRef
Earlier:
A phase field higher-order active contour model of directed networks,
NORDIA09(398-404).
IEEE DOI 0910
BibRef
Earlier:
Phase diagram of a long bar under a higher-order active contour energy: Application to hydrographic network extraction from VHR satellite images,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Peng, T.[Ting], Jermyn, I.H.[Ian H.], Prinet, V.[Véronique], Zerubia, J.B.[Josiane B.],
Extended Phase Field Higher-Order Active Contour Models for Networks: Its Application to Road Network Extraction from VHR Satellite Images,
IJCV(88), No. 1, May 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
An Extended Phase Field Higher-Order Active Contour Model for Networks and Its Application to Road Network Extraction from VHR Satellite Images,
ECCV08(III: 509-520).
Springer DOI 0810
BibRef
Earlier:
Extraction of Main and Secondary Roads in VHR Images Using A Higher-Order Phase Field Model,
ISPRS08(B3a: 215 ff).
PDF File. 0807
BibRef

Rochery, M.[Marie], Jermyn, I.H.[Ian H.], Zerubia, J.B.[Josiane B.],
Higher-Order Active Contour Energies for Gap Closure,
JMIV(29), No. 1, Septmeber 2007, pp. 1-20.
Springer DOI 0709
BibRef
Earlier:
Gap closure in (road) networks using higher-order active contours,
ICIP04(III: 1879-1882).
IEEE DOI 0505
BibRef

Peng, T., Jermyn, I.H., Prinet, V., Zerubia, J.B., Hu, B.,
A phase field model incorporating generic and specific prior knowledge applied to road network extraction from VHR satellite images,
BMVC07(xx-yy).
PDF File. 0709
BibRef

El Ghoul, A.[Aymen], Jermyn, I.H.[Ian H.], Zerubia, J.B.[Josiane B.],
Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model,
PCVIA10(A:215).
PDF File. 1009
Rivers, as regions. BibRef

Stoica, R.[Radu], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
A Gibbs Point Process for Road Extraction from Remotely Sensed Images,
IJCV(57), No. 2, May 2004, pp. 121-136.
DOI Link 0402
BibRef

Lacoste, C., Descombes, X., Zerubia, J.B.,
Road network extraction in remote sensing by a Markov object process,
ICIP03(III: 1017-1020).
IEEE DOI 0312
BibRef

Lacoste, C.[Caroline], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Point Processes for Unsupervised Line Network Extraction in Remote Sensing,
PAMI(27), No. 10, October 2005, pp. 1568-1579.
IEEE DOI 0509
BibRef
Earlier:
A Comparative Study of Point Processes for Line Network Extraction i,
INRIARR-4516, July 2002.
HTML Version. 0211
BibRef

Lacoste, C.[Caroline], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Unsupervised line network extraction in remote sensing using a polyline process,
PR(43), No. 4, April 2010, pp. 1631-1641.
Elsevier DOI 1002
Line network extraction; Aerial and satellite images; Stochastic geometry; Marked point process; Simulated annealing; RJMCMC BibRef

Dong, Y.H., Forster, B.C., Ticehurst, C.,
Street Orientation Detection and Recognition in Landsat TM and SPOT HRV Imagery,
PRL(18), No. 8, August 1997, pp. 759-769. 9801
BibRef

Zhang, Y.[Yun],
A Method for Continuous Extraction of Multispectrally Classified Urban Rivers,
PhEngRS(66), No. 8, August 2000, pp. 991-1000. By applying this method, discontinuous river segments can be connected, small water areas can be separated from noise, and noise in large water areas can be eliminated. 0008
BibRef

Doucette, P.[Peter], Agouris, P.[Peggy], Stefanidis, A.[Anthony], Musavi, M.[Mohamad],
Self-organised clustering for road extraction in classified imagery,
PandRS(55), No. 5-6, March 2001, pp. 347-358.
HTML Version. Semi-automated procedure. For moderate resolution images (2M GSD), find elongated regions in classified MSI data. 0105
BibRef

Agouris, P., Doucette, P., Stefanidis, A.,
Spatiospectral Cluster Analysis of Elongated Regions in Aerial Imagery,
ICIP01(II: 789-792).
IEEE DOI 0108
Extend the PandRS paper above to automate the road seed finder. Generate classification with 4 classes. Choose the on that best fits a road model. Link the elongated regions with MST approach. BibRef

Shi, W.Z.[Wen-Zhong], Zhu, C.Q.[Chang-Qing],
The line segment match method for extracting road network from high-resolution satellite images,
GeoRS(40), No. 2, February 2002, pp. 511-514.
IEEE Top Reference. 0205
BibRef

Kim, T.[Taejung], Park, S.R.[Seung-Ran],
Road extraction from images using template matching,
US_Patent6,721,660, Apr 13, 2004
WWW Link. BibRef 0404

Kozaitis, S.P.[Samuel P.], Cofer, R.H.,
Lineal Feature Detection Using Multiresolution Wavelet Filters,
PhEngRS(71), No. 6, June 2005, pp. 689-698.
WWW Link. 0509
Detection of road seed pixels to reduce the number of false positives.
See also Extended Hough transform for linear feature detection. BibRef

Amo, M., Martinez, F., Torre, M.,
Road Extraction from Aerial Images Using a Region Competition Algorithm,
IP(15), No. 5, May 2006, pp. 1192-1201.
IEEE DOI 0605

See also Agricultural-Field Extraction on Aerial Images by Region Competition Algorithm. BibRef

Zhou, J.[Jun], Bischof, W.F.[Walter F.], Caelli, T.M.[Terry M.],
Road tracking in aerial images based on human-computer interaction and Bayesian filtering,
PandRS(61), No. 2, November 2006, pp. 108-124.
Elsevier DOI 0703
BibRef
Earlier:
Robust and Efficient Road Tracking in Aerial Images,
CMRT05(xx-yy).
PDF File. 0508
Road tracking; Aerial images; Human-computer interaction; Bayesian filtering; Particle filter; Extended Kalman filter BibRef

Zhou, J.[Jun], Cheng, L., Bischof, W.F.[Walter F.],
Online Learning With Novelty Detection in Human-Guided Road Tracking,
GeoRS(45), No. 12, December 2007, pp. 3967-3977.
IEEE DOI 0711
BibRef

Wang, Y., Bai, L., Fairhurst, M.,
Robust Road Modeling and Tracking Using Condensation,
ITS(9), No. 4, December 2008, pp. 570-579.
IEEE DOI 0812
BibRef

Álvarez, J.M.[Jose M.], Gevers, T.[Theo], López, A.M.[Antonio M.],
Learning Photometric Invariance for Object Detection,
IJCV(90), No. 1, October 2010, pp. xx-yy.
Springer DOI 1007
BibRef
Earlier:
3D Scene priors for road detection,
CVPR10(57-64).
IEEE DOI 1006
BibRef
Earlier:
Learning photometric invariance from diversified color model ensembles,
CVPR09(565-572).
IEEE DOI 0906
BibRef
And:
Vision-based road detection using road models,
ICIP09(2073-2076).
IEEE DOI 0911

See also Evaluating Color Representations for On-Line Road Detection. BibRef

Alvarez, J.M.[Jose M.], Salzmann, M.[Mathieu], Barnes, N.M.[Nick M.],
Data-driven road detection,
WACV14(1134-1141)
IEEE DOI 1406
Detectors BibRef

Alvarez, J.M.[Jose M.], Salzmann, M.[Mathieu], Barnes, N.M.[Nick M.],
Efficient transductive semantic segmentation,
WACV16(1-9)
IEEE DOI 1606
BibRef
And:
Large-scale semantic co-labeling of image sets,
WACV14(501-508)
IEEE DOI 1406
Bicycles; Birds; Boats; Face; Roads; Training BibRef

Alvarez, J.M.[Jose M.], Gevers, T.[Theo], Le Cun, Y.L.[Yann L.], Lopez, A.M.[Antonio M.],
Road Scene Segmentation from a Single Image,
ECCV12(VII: 376-389).
Springer DOI 1210
BibRef
And: A1, A3, A2, A4:
Semantic Road Segmentation via Multi-scale Ensembles of Learned Features,
CVVT12(II: 586-595).
Springer DOI 1210
BibRef

Álvarez, J.M.[Jose M.], López, A.M.[Antonio M.],
Road Detection Based on Illuminant Invariance,
ITS(12), No. 1, March 2011, pp. 184-193.
IEEE DOI 1103
BibRef

Skoglar, P., Orguner, U., Törnqvist, D., Gustafsson, F.,
Road Target Search and Tracking with Gimballed Vision Sensor on an Unmanned Aerial Vehicle,
RS(4), No. 7, July 2012, pp. 2076-2111.
DOI Link 1208
BibRef

Koller, M.[Mathias], Butenuth, M.[Matthias], Gerke, M.[Markus],
Automatic Road-Tracking in Airborne Image Sequences,
PFG(2010), No. 5, 2010, pp. 327-338.
WWW Link. 1211
BibRef

Cao, C.Q.[Chu-Qing], Sun, Y.[Ying],
Automatic Road Centerline Extraction from Imagery Using Road GPS Data,
RS(6), No. 9, 2014, pp. 9014-9033.
DOI Link 1410
BibRef

Zhou, H., Kong, H., Wei, L., Creighton, D., Nahavandi, S.,
Efficient Road Detection and Tracking for Unmanned Aerial Vehicle,
ITS(16), No. 1, February 2015, pp. 297-309.
IEEE DOI 1502
Cameras BibRef

Zhou, H., Kong, H., Wei, L., Creighton, D., Nahavandi, S.,
On Detecting Road Regions in a Single UAV Image,
ITS(18), No. 7, July 2017, pp. 1713-1722.
IEEE DOI 1706
Geometry, Image color analysis, Image edge detection, Image segmentation, Roads, Satellites, Unmanned aerial vehicles, Road detection, aerial images, remote sensing, segmentation, stroke width transform (SWT), unmanned, aerial, vehicles, (UAV) BibRef

Sujatha, C.[Chinnathevar], Selvathi, D.[Dharmar],
Connected component-based technique for automatic extraction of road centerline in high resolution satellite images,
JIVP(2015), No. 1, 2015, pp. 8.
DOI Link 1504
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Gao, L.P.[Li-Peng], Shi, W.Z.[Wen-Zhong], Miao, Z.[Zelang], Lv, Z.Y.[Zhi-Yong],
Method Based on Edge Constraint and Fast Marching for Road Centerline Extraction from Very High-Resolution Remote Sensing Images,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
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Zhou, T.T.[Ting-Ting], Sun, C.L.[Cheng-Lin], Fu, H.Y.[Hao-Yang],
Road Information Extraction from High-Resolution Remote Sensing Images Based on Road Reconstruction,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link 1901
Road centerline extraction, road width extraction, broken centerline connection, and road reconstruction. BibRef

Wu, H.[Hangbin], Xu, Z.[Zeran], Wu, G.J.[Guang-Jun],
A Novel Method of Missing Road Generation in City Blocks Based on Big Mobile Navigation Trajectory Data,
IJGI(8), No. 3, 2019, pp. xx-yy.
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Liu, Y.[Yi], Li, W.J.[Wen-Jing],
A New Algorithms of Stroke Generation Considering Geometric and Structural Properties of Road Network,
IJGI(8), No. 7, 2019, pp. xx-yy.
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Tao, C.[Chao], Qi, J.[Ji], Li, Y.S.[Yan-Sheng], Wang, H.[Hao], Li, H.F.[Hai-Feng],
Spatial information inference net: Road extraction using road-specific contextual information,
PandRS(158), 2019, pp. 155-166.
Elsevier DOI 1912
Road extraction, Semantic segmentation, Spatial information inference structure, Road-specific contextual information BibRef

Dai, J.G.[Ji-Guang], Li, C.C.[Cheng-Cheng], Zuo, Y.Q.[Yu-Qiang], Ai, H.B.[Hai-Bin],
An OSM Data-Driven Method for Road-Positive Sample Creation,
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DOI Link 2011
OpenStreetMap data. Samples for deep learning. BibRef

Li, X., Wang, Y., Zhang, L., Liu, S., Mei, J., Li, Y.,
Topology-Enhanced Urban Road Extraction via a Geographic Feature-Enhanced Network,
GeoRS(58), No. 12, December 2020, pp. 8819-8830.
IEEE DOI 2012
Roads, Feature extraction, Image edge detection, Remote sensing, Machine learning, Topology, Network topology, topology relationship BibRef

Iqbal, J.[Javed], Masood, A.[Aliza], Sultani, W.[Waqas], Ali, M.[Mohsen],
Leveraging topology for domain adaptive road segmentation in satellite and aerial imagery,
PandRS(206), 2023, pp. 106-117.
Elsevier DOI Code:
WWW Link. 2312
Remote sensing, Road segmentation, Domain adaptation, Self-training, Deep learning, Sustainable cities and communities BibRef


Wu, X.[Xindi], Lau, K.[KwunFung], Ferroni, F.[Francesco], Ošep, A.[Aljoša], Ramanan, D.[Deva],
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road detection, convolutional network, connected tube model, MPP, road tracking BibRef

Zhou, S.G.[Shao-Guang], Lu, G.J.[Guo-Jun], Teng, S.W.[Shyh Wei], Zhang, D.S.[Deng-Sheng],
Extracting road centrelines from binary road images by optimizing geodesic lines,
ICVNZ15(1-6)
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dynamic programming BibRef

Maarir, A., Bouikhalene, B.,
Roads Detection from Satellite Images Based on Active Contour Model and Distance Transform,
CGiV16(94-98)
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MultiTemp11(237-240).
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Hashemi, S., Valadan Zoej, M.J., Mokhtarzadeh, M.,
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AIPR04(16-21).
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AIPR06(12-12).
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AIPR05(166-172).
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AIPR03(157-160).
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ACIVS06(1151-1162).
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Sawano, H., Okada, M.,
Road extraction by snake with inertia and differential features,
ICPR04(IV: 380-383).
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Rasmussen, C.,
Grouping dominant orientations for ill-structured road following,
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Bicego, M., Dalfini, S., Vernazza, G., Murino, P.,
Automatic road extraction from aerial images by probabilistic contour tracking,
ICIP03(III: 585-588).
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Keaton, T., Brokish, J.,
Evolving roads in Ikonos multispectral imagery,
ICIP03(III: 1001-1004).
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Earlier:
A level set method for the extraction of roads from multispectral imagery,
AIPR02(141-147).
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Faber, A.[Annett], Förstner, W.[Wolfgang],
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Tesser, H.[Herbert], Pavlidis, T.[Theo],
RoadFinder Front End: an Automated Road Extraction System,
ICPR00(Vol I: 338-341).
IEEE DOI 0009
Looks almost like find apars and link them filter short ones. BibRef

Duta, N.[Nicolae],
Road Detection in Panchromatic SPOT Satellite Images,
ICPR00(Vol IV: 308-311).
IEEE DOI 0009
From seeds combine and generate road tree. Low resolution roads. BibRef

Price, K.E.[Keith E.],
Urban Street Grid Description and Verification,
WACV00(148-154).
IEEE DOI 0010
BibRef USC Computer VisionModel based approach.
PDF File. BibRef

Price, K.E.[Keith E.],
Road Grid Extraction and Verification,
ISPRSGIS99(101-106). BibRef 9900 USC Computer VisionModel based approach to find urban grid patterns.
PDF File. BibRef

Borkowski, A., Burghardt, D., Meier, S.,
A Fast Snakes Algorithm Using the Tangent Angle Function,
ISPRSGIS99(61-66). Snakes for road descriptions. BibRef 9900

Rianto, Y., Kondo, S., Kim, T.,
Detection of roads from satellite image using the optimal search,
CIAP99(804-809).
IEEE DOI 9909
BibRef

McKeown, D.M., and Denlinger, J.L.[Jerry L.],
Cooperative Methods for Road Tracking in Aerial Imagery,
DARPA88(327-341). BibRef 8800
And: CVPR88(662-672).
IEEE Abstract. Roads are extracted using several types of road tracking with the choice depending on which one is doing the best. BibRef

Vosselman, G., and de Knecht, J.,
Road Tracing by Profile Matching and Kalman Filtering,
Ascona95(265-274). Tracking approach. BibRef 9500

Hu, J., Sakoda, B., Pavlidis, T.,
Interactive Road Finding For Aerial Images,
WACV92(56-63).
IEEE DOI BibRef 9200

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Road Network Model Integration, Updating, and Change Detection .


Last update:Mar 16, 2024 at 20:36:19