18.9.6 Aerial Vehicle Based Structure, UAV, Depth, and Shape from Motion

Chapter Contents (Back)
Motion, Structure. Shape from Motion. Navigation.
See also Visual Odometry, Distance Measurments from Vision, Motion.

Sridhar, B., Suorsa, R.E., Hussien, B.,
Passive Range Estimation for Rotorcraft Low-Altitude Flight,
MVA(6), 1993, pp. 10-24. BibRef 9300

Mancini, F.[Francesco], Dubbini, M.[Marco], Gattelli, M.[Mario], Stecchi, F.[Francesco], Fabbri, S.[Stefano], Gabbianelli, G.[Giovanni],
Using Unmanned Aerial Vehicles (UAV) for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments,
RS(5), No. 12, 2013, pp. 6880-6898.
DOI Link 1402
BibRef

Westfeld, P.[Patrick], Mader, D.[David], Maas, H.G.[Hans-Gerd],
Generation of TIR-attributed 3D Point Clouds from UAV-based Thermal Imagery,
PFG(2015), No. 5, 2015, pp. 381-393.
DOI Link 1512
Thermal IR. Structure from motion. BibRef

Shao, Z.F.[Zhen-Feng], Yang, N.[Nan], Xiao, X.W.[Xiong-Wu], Zhang, L.[Lei], Peng, Z.[Zhe],
A Multi-View Dense Point Cloud Generation Algorithm Based on Low-Altitude Remote Sensing Images,
RS(8), No. 5, 2016, pp. 381.
DOI Link 1606
BibRef

Sturdivant, E.J.[Emily J.], Lentz, E.E.[Erika E.], Thieler, E.R.[E. Robert], Farris, A.S.[Amy S.], Weber, K.M.[Kathryn M.], Remsen, D.P.[David P.], Miner, S.[Simon], Henderson, R.E.[Rachel E.],
UAS-SfM for Coastal Research: Geomorphic Feature Extraction and Land Cover Classification from High-Resolution Elevation and Optical Imagery,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
Shape from motion. BibRef

Koci, J.[Jack], Jarihani, B.[Ben], Leon, J.X.[Javier X.], Sidle, R.C.[Roy C.], Wilkinson, S.N.[Scott N.], Bartley, R.[Rebecca],
Assessment of UAV and Ground-Based Structure from Motion with Multi-View Stereo Photogrammetry in a Gullied Savanna Catchment,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Jiang, S.[San], Jiang, W.[Wanshou],
Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion,
PandRS(132), No. 1, 2017, pp. 140-161.
Elsevier DOI 1710
Unmanned aerial vehicle BibRef

Jiang, S.[San], Jiang, W.[Wanshou],
Hierarchical motion consistency constraint for efficient geometrical verification in UAV stereo image matching,
PandRS(142), 2018, pp. 222-242.
Elsevier DOI 1807
Unmanned aerial vehicle, Geometrical verification, Motion consistency constraint, Image matching, Spatial matching BibRef

Sanz-Ablanedo, E.[Enoc], Chandler, J.H.[Jim H.], Rodríguez-Pérez, J.R.[José Ramón], Ordóñez, C.[Celestino],
Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Jiang, S.[San], Jiang, W.[Wanshou],
Efficient SfM for Oblique UAV Images: From Match Pair Selection to Geometrical Verification,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Huang, Y., Sithole, L., Lee, T.,
Structure From Motion Technique for Scene Detection Using Autonomous Drone Navigation,
SMCS(49), No. 12, December 2019, pp. 2559-2570.
IEEE DOI 1912
Drones, Feature extraction, Streaming media, Cameras, Global Positioning System, structure from motion (SfM) BibRef

Jiang, S.[San], Jiang, C.[Cheng], Jiang, W.S.[Wan-Shou],
Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools,
PandRS(167), 2020, pp. 230-251.
Elsevier DOI 2008
Unmanned aerial vehicle, Structure-from-motion, Bundle adjustment, Match pair selection, Outlier removal, Divide-and-conquer BibRef

de Marco, J.[Jessica], Maset, E.[Eleonora], Cucchiaro, S.[Sara], Beinat, A.[Alberto], Cazorzi, F.[Federico],
Assessing Repeatability and Reproducibility of Structure-from-Motion Photogrammetry for 3D Terrain Mapping of Riverbeds,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef


Pirvu, M.[Mihai], Robu, V.[Victor], Licaret, V.[Vlad], Costea, D.[Dragos], Marcu, A.[Alina], Slusanschi, E.[Emil], Sukthankar, R.[Rahul], Leordeanu, M.[Marius],
Depth distillation: unsupervised metric depth estimation for UAVs by finding consensus between kinematics, optical flow and deep learning,
EVW21(3209-3217)
IEEE DOI 2109
Measurement, Deep learning, Training, Geometry, Pipelines, Estimation, Kinematics BibRef

Leotta, M.J., Smith, E., Dawkins, M., Tunison, P.,
Open source structure-from-motion for aerial video,
WACV16(1-9)
IEEE DOI 1606
Algorithm design and analysis BibRef

Caroti, G., Martínez-Espejo Zaragoza, I., Piemonte, A.,
Accuracy Assessment in Structure from Motion 3D Reconstruction from UAV-Born Images: The Influence of the Data Processing Methods,
UAV-g15(103-109).
DOI Link 1512
BibRef

Zingoni, A.[Andrea], Diani, M.[Marco], Corsini, G.[Giovanni], Masini, A.,
Real-Time 3D Reconstruction from Images Taken from an UAV,
GeoUAV15(313-319).
DOI Link 1602
BibRef

Mader, D., Blaskow, R., Westfeld, P., Maas, H.G.,
UAV-Based Acquisition of 3D Point Cloud: A Comparison of a Low-Cost Laser Scanner and SFM-Tools,
GeoUAV15(335-341).
DOI Link 1602
BibRef

Wendel, A.[Andreas], Maurer, M.[Michael], Graber, G.[Gottfried], Pock, T.[Thomas], Bischof, H.[Horst],
Dense reconstruction on-the-fly,
CVPR12(1450-1457).
IEEE DOI 1208
Literally. micro-aerial vehicle. BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Ground Vehicle Based Structure, Depth, and Shape from Motion .


Last update:Oct 24, 2021 at 16:35:58