Song, W.B.[Wen-Bo],
Haithcoat, T.L.,
Development of comprehensive accuracy assessment indexes for building
footprint extraction,
GeoRS(43), No. 2, February 2005, pp. 402-404.
IEEE Abstract.
0501
BibRef
Zhang, K.,
Yan, J.,
Chen, S.C.,
Automatic Construction of Building Footprints From Airborne LIDAR Data,
GeoRS(44), No. 9, September 2006, pp. 2523-2533.
IEEE DOI
0609
BibRef
Yan, J.H.[Jian-Hua],
Zhang, K.[Keqi],
Zhang, C.C.[Cheng-Cui],
Chen, S.C.[Shu-Ching],
Narasimhan, G.,
Automatic Construction of 3-D Building Model From Airborne LIDAR Data
Through 2-D Snake Algorithm,
GeoRS(53), No. 1, January 2015, pp. 3-14.
IEEE DOI
1410
airborne radar
BibRef
Gamba, P.[Paolo],
Dell'Acqua, F.[Fabio],
Lisini, G.[Gianni],
Cisotta, F.[Francesco],
Improving Building Footprints in InSAR Data by Comparison with a Lidar
DSM,
PhEngRS(72), No. 1, January 2006, pp. 63-70.
WWW Link. The combination of three-dimensional laser and radar data for improved
building extraction.
0602
BibRef
Vallet, B.[Bruno],
Pierrot-Deseilligny, M.[Marc],
Boldo, D.[Didier],
Brédif, M.[Mathieu],
Building footprint database improvement for 3D reconstruction:
A split and merge approach and its evaluation,
PandRS(66), No. 5, September 2011, pp. 732-742.
Elsevier DOI
1110
BibRef
Earlier: A1, A2, A3, Only:
Building Footprint Database Improvement for 3D Reconstruction:
A Direction Aware Split and Merge Approach,
CMRT09(139-144).
PDF File.
0909
Photogrammetry; Segmentation; Reconstruction; Urban scene; Building
BibRef
Bredif, M.,
Boldo, D.,
Pierrot-Deseilligny, M.,
Maitre, H.,
3D Building Reconstruction with Parametric Roof Superstructures,
ICIP07(II: 537-540).
IEEE DOI
0709
BibRef
Tournaire, O.[Olivier],
Bredif, M.,
Boldo, D.,
Durupt, M.,
An efficient stochastic approach for building footprint extraction from
digital elevation models,
PandRS(65), No. 4, July 2010, pp. 317-327.
Elsevier DOI
1003
Digital Elevation Model; Building footprint; Energetic modeling;
Marked point processes; RJMCMC
BibRef
Brédif, M.[Mathieu],
Tournaire, O.[Olivier],
Vallet, B.[Bruno],
Champion, N.[Nicolas],
Extracting polygonal building footprints from digital surface models:
A fully-automatic global optimization framework,
PandRS(77), No. 1, March 2013, pp. 57-65.
Elsevier DOI
1303
Urban; Building; Modeling; Geometry; Analysis; DEM/DTM
BibRef
Ferro, A.,
Brunner, D.,
Bruzzone, L.,
Automatic Detection and Reconstruction of Building Radar Footprints
From Single VHR SAR Images,
GeoRS(51), No. 2, February 2013, pp. 935-952.
IEEE DOI
1302
Cited by 1
BibRef
Gilani, S.A.N.[Syed Ali Naqi],
Awrangjeb, M.[Mohammad],
Lu, G.J.[Guo-Jun],
An Automatic Building Extraction and Regularisation Technique Using
LiDAR Point Cloud Data and Orthoimage,
RS(8), No. 3, 2016, pp. 258.
DOI Link
1604
BibRef
And:
Robust building roof segmentation using airborne point cloud data,
ICIP16(859-863)
IEEE DOI
1610
BibRef
And:
Fusion of LIDAR Data and Multispectral Imagery for Effective Building
Detection Based on Graph and Connected Component Analysis,
PIA15(65-72).
DOI Link
1504
BibRef
And: A2, A3, Only:
A triangulation-based technique for building boundary identification
from point cloud data,
ICVNZ15(1-6)
IEEE DOI
1701
BibRef
And: A2, A3, Only:
Automatic Building Footprint Extraction and Regularisation from LIDAR
Point Cloud Data,
DICTA14(1-8)
IEEE DOI
1502
buildings (structures).
Buildings
digital elevation models
See also Automatic Extraction of Building Roofs Using LIDAR Data and Multispectral Imagery.
BibRef
Dey, E.K.[Emon Kumar],
Awrangjeb, M.[Mohammad],
Kurdi, F.T.[Fayez Tarsha],
Stantic, B.[Bela],
Building Boundary Extraction from LiDAR Point Cloud Data,
DICTA21(1-6)
IEEE DOI
2201
Point cloud compression, Measurement, Image segmentation,
Laser radar, Shape, Digital images, boundary extraction,
Performance metric
BibRef
Awrangjeb, M.,
Lu, G.J.[Guo-Jun],
Fraser, C.S.,
Automatic Building Extraction From LIDAR Data Covering Complex Urban
Scenes,
PCV14(25-32).
DOI Link
1404
BibRef
Earlier: A1, A2, Only:
Building Roof Plane Extraction from LIDAR Data,
DICTA13(1-8)
IEEE DOI
1402
geophysical image processing
BibRef
Awrangjeb, M.[Mohammad],
Ravanbakhsh, M.[Mehdi],
Fraser, C.S.[Clive S.],
Automatic Detection of Residential Buildings Using LIDAR Data and
Multispectral Imagery,
PandRS(65), No. 5, September 2010, pp. 457-467.
Elsevier DOI
1003
BibRef
And:
Building Detection from Multispectral Imagery and LIDAR Data Employing
A Threshold-Free Evaluation System,
PCVIA10(A:49).
PDF File.
1009
BibRef
And:
Automatic Building Detection Using LIDAR Data and Multispectral Imagery,
DICTA10(45-51).
IEEE DOI
1012
Building detection; LIDAR; Point cloud; Multispectral imagery; Fusion
BibRef
Li, J.Z.[Jing-Zhong],
Li, X.G.[Xin-Gong],
Xie, T.[Tian],
Morphing of Building Footprints Using a Turning Angle Function,
IJGI(6), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Zhuo, X.Y.[Xiang-Yu],
Fraundorfer, F.[Friedrich],
Kurz, F.[Franz],
Reinartz, P.[Peter],
Optimization of OpenStreetMap Building Footprints Based on Semantic
Information of Oblique UAV Images,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Li, W.J.[Wei-Jia],
He, C.H.[Cong-Hui],
Fang, J.R.[Jia-Rui],
Zheng, J.P.[Jue-Peng],
Fu, H.H.[Hao-Huan],
Yu, L.[Le],
Semantic Segmentation-Based Building Footprint Extraction Using Very
High-Resolution Satellite Images and Multi-Source GIS Data,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Earlier: A1, A2, A3, A5, Only:
Semantic Segmentation Based Building Extraction Method Using
Multi-source GIS Map Datasets and Satellite Imagery,
DeepGlobe18(233-2333)
IEEE DOI
1812
Buildings, Satellites, Urban areas, Semantics, Image segmentation,
Training, Data mining
BibRef
Bagheri, H.[Hossein],
Schmitt, M.[Michael],
Zhu, X.X.[Xiao-Xiang],
Fusion of Multi-Sensor-Derived Heights and OSM-Derived Building
Footprints for Urban 3D Reconstruction,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Schuegraf, P.[Philipp],
Bittner, K.[Ksenia],
Automatic Building Footprint Extraction from Multi-Resolution Remote
Sensing Images Using a Hybrid FCN,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Bittner, K.,
Cui, S.,
Reinartz, P.,
Building Extraction From Remote Sensing Data Using Fully Convolutional
Networks,
Hannover17(481-486).
DOI Link
1805
BibRef
Pasquali, G.[Giorgio],
Iannelli, G.C.[Gianni Cristian],
Dell'Acqua, F.[Fabio],
Building Footprint Extraction from Multispectral, Spaceborne Earth
Observation Datasets Using a Structurally Optimized U-Net
Convolutional Neural Network,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Liu, P.H.[Peng-Hua],
Liu, X.P.[Xiao-Ping],
Liu, M.X.[Meng-Xi],
Shi, Q.[Qian],
Yang, J.X.[Jin-Xing],
Xu, X.C.[Xiao-Cong],
Zhang, Y.Y.[Yuan-Ying],
Building Footprint Extraction from High-Resolution Images via Spatial
Residual Inception Convolutional Neural Network,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Wei, S.,
Ji, S.,
Lu, M.,
Toward Automatic Building Footprint Delineation From Aerial Images
Using CNN and Regularization,
GeoRS(58), No. 3, March 2020, pp. 2178-2189.
IEEE DOI
2003
Building extraction, fully convolutional network (FCN),
polygon regularization, segmentation
BibRef
Li, Q.,
Shi, Y.,
Huang, X.,
Zhu, X.X.,
Building Footprint Generation by Integrating Convolution Neural
Network With Feature Pairwise Conditional Random Field (FPCRF),
GeoRS(58), No. 11, November 2020, pp. 7502-7519.
IEEE DOI
2011
Buildings, Semantics, Feature extraction, Image segmentation,
Task analysis, Remote sensing, Computer architecture,
semantic segmentation
BibRef
Sun, Y.[Yao],
Montazeri, S.[Sina],
Wang, Y.Y.[Yuan-Yuan],
Zhu, X.X.[Xiao Xiang],
Automatic registration of a single SAR image and GIS building
footprints in a large-scale urban area,
PandRS(170), 2020, pp. 1-14.
Elsevier DOI
2011
GIS building footprints, Large-scale, Registration, SAR image, Urban area
BibRef
Milosavljevic, A.[Aleksandar],
Automated Processing of Remote Sensing Imagery Using Deep Semantic
Segmentation: A Building Footprint Extraction Case,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Gautam, D.,
Lucieer, A.,
Bendig, J.,
Malenovský, Z.,
Footprint Determination of a Spectroradiometer Mounted on an Unmanned
Aircraft System,
GeoRS(58), No. 5, May 2020, pp. 3085-3096.
IEEE DOI
2005
Spectroradiometers, Global navigation satellite system, Antennas,
Geology, Vegetation mapping, Cameras, Synchronization,
unmanned aircraft system (UAS)
BibRef
Liao, C.[Cheng],
Hu, H.[Han],
Li, H.F.[Hai-Feng],
Ge, X.M.[Xu-Ming],
Chen, M.[Min],
Li, C.N.[Chuang-Nong],
Zhu, Q.[Qing],
Joint Learning of Contour and Structure for Boundary-Preserved
Building Extraction,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Zhu, Q.[Qing],
Liao, C.[Cheng],
Hu, H.[Han],
Mei, X.M.[Xiao-Ming],
Li, H.F.[Hai-Feng],
MAP-Net: Multiple Attending Path Neural Network for Building
Footprint Extraction From Remote Sensed Imagery,
GeoRS(59), No. 7, July 2021, pp. 6169-6181.
IEEE DOI
2106
Feature extraction, Buildings, Semantics, Data mining,
Spatial resolution, Remote sensing, Convolution,
semantic segmentation
BibRef
Touzani, S.[Samir],
Granderson, J.[Jessica],
Open Data and Deep Semantic Segmentation for Automated Extraction of
Building Footprints,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Ayala, C.[Christian],
Sesma, R.[Rubén],
Aranda, C.[Carlos],
Galar, M.[Mikel],
A Deep Learning Approach to an Enhanced Building Footprint and Road
Detection in High-Resolution Satellite Imagery,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Wei, X.C.[Xin-Chun],
Li, X.[Xing],
Liu, W.[Wei],
Zhang, L.P.[Lian-Peng],
Cheng, D.[Dayu],
Ji, H.Y.[Han-Yu],
Zhang, W.Z.[Wen-Zheng],
Yuan, K.[Kai],
Building Outline Extraction Directly Using the U2-Net Semantic
Segmentation Model from High-Resolution Aerial Images and a
Comparison Study,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Li, Z.M.[Zi-Ming],
Xin, Q.C.[Qin-Chuan],
Sun, Y.[Ying],
Cao, M.Y.[Meng-Ying],
A Deep Learning-Based Framework for Automated Extraction of Building
Footprint Polygons from Very High-Resolution Aerial Imagery,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Daranagama, S.[Samitha],
Witayangkurn, A.[Apichon],
Automatic Building Detection with Polygonizing and Attribute
Extraction from High-Resolution Images,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Liu, C.[Chun],
Hu, Y.[Yaohui],
Li, Z.[Zheng],
Xu, J.[Junkui],
Han, Z.G.[Zhi-Gang],
Guo, J.Z.[Jian-Zhong],
TriangleConv: A Deep Point Convolutional Network for Recognizing
Building Shapes in Map Space,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Yan, X.F.[Xiong-Feng],
Chen, H.[Huan],
Huang, H.[Haoran],
Liu, Q.[Qian],
Yang, M.[Min],
Building Typification in Map Generalization Using Affinity
Propagation Clustering,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Wei, S.Q.[Shi-Qing],
Ji, S.P.[Shun-Ping],
Graph Convolutional Networks for the Automated Production of Building
Vector Maps From Aerial Images,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI
2112
Buildings, Feature extraction, Remote sensing, Image segmentation,
Detectors, Data mining, Production, Building extraction,
polygon regularization
BibRef
Guo, H.[Haonan],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Su, X.[Xin],
A coarse-to-fine boundary refinement network for building footprint
extraction from remote sensing imagery,
PandRS(183), 2022, pp. 240-252.
Elsevier DOI
2201
Building footprint extraction, Boundary refinement, Coarse-to-fine
BibRef
Girard, N.[Nicolas],
Smirnov, D.[Dmitriy],
Solomon, J.[Justin],
Tarabalka, Y.[Yuliya],
Polygonal Building Extraction by Frame Field Learning,
CVPR21(5887-5896)
IEEE DOI
2111
Training, Image segmentation, Shape, Buildings,
Prediction algorithms, Skeleton, Task analysis
BibRef
Ashiotis, G.[Giannis],
Oldfield, J.[James],
Chrysostomou, C.[Charalambos],
Christoudias, T.[Theodoros],
Nicolaou, M.A.[Mihalis A.],
Shared-space Autoencoders with Randomized Skip Connections for Building
Footprint Detection with Missing Views,
PRRS20 (536-549).
Springer DOI
2103
BibRef
Bischke, B.,
Helber, P.,
Folz, J.,
Borth, D.,
Dengel, A.,
Multi-Task Learning for Segmentation of Building Footprints with Deep
Neural Networks,
ICIP19(1480-1484)
IEEE DOI
1910
Deep Learning, Semantic Segmentation, Satellite Imagery,
Multi Task Learning, Building Extraction
BibRef
Khoshboresh Masouleh, M.,
Saradjian, M.R.,
Robust Building Footprint Extraction From Big Multi-sensor Data Using
Deep Competition Network,
SMPR19(615-621).
DOI Link
1912
BibRef
Dickenson, M.,
Gueguen, L.,
Rotated Rectangles for Symbolized Building Footprint Extraction,
DeepGlobe18(215-2153)
IEEE DOI
1812
Buildings, Computer architecture, Microprocessors, Architecture,
Urban areas, Satellites
BibRef
Linh, T.H.[Truong-Hong],
Laefer, D.F.[Debra F.],
Yang, B.S.[Bi-Sheng],
Huang, R.G.[Rong-Gang],
Li, J.P.[Jian-Ping],
IQPC 2015 Track: Evaluation of Automatically Generated 2D Footprints
from Urban Lidar Data,
GeoBigData15(527-534).
DOI Link
1602
BibRef
Li, Y.,
Zhu, L.,
Shimamura, H.,
Tachibana, K.,
A Refining Method For Building Object Aggregation And Footprint
Modelling Using Multi-source Data,
ISPRS12(XXXIX-B3:41-46).
DOI Link
1209
BibRef
Dini, G.R.,
Jacobsen, K.,
Heipke, C.,
Delineation of Building Footprints from High Resolution Satellite
Stereo Imagery Using Image Matching and a GIS Database,
Hannover13(81-85).
DOI Link
1308
See also 3D Building Change Detection Using High Resolution Stereo Images and a GIS Database.
See also procedure for semi-Automatic Orthophoto Generation from High Resolution Satellite Imagery, A.
BibRef
Michelin, J.C.,
Mallet, C.,
David, N.,
Building Edge Detection Using Small-footprint Airborne Full-waveform
Lidar Data,
AnnalsPRS(I-3), No. 2012, pp. 147-152.
HTML Version.
1209
BibRef
Yan, L.[Lili],
Zhang, J.X.[Ji-Xian],
Huang, G.[Guoman],
Zhao, Z.[Zheng],
Building Footprints Extraction from PolSAR Image Using Multi-Features
and Edge Information,
ISIDF11(1-5).
IEEE DOI
1111
BibRef
Wang, O.[Oliver],
Lodha, S.K.[Suresh K.],
Helmbold, D.P.[David P.],
A Bayesian Approach to Building Footprint Extraction from Aerial LIDAR
Data,
3DPVT06(192-199).
IEEE DOI
0606
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Roof Structure, 3-D .