12.3.4.1.7 Point Cloud Change Detection, Registration

Chapter Contents (Back)
Registration, 3-D. Change Detection. LiDAR. LiDAR, Change Detection. TLS.

Shrestha, R.L., Carter, W.E., Sartori, M., Luzum, B.J., Slatton, K.C.,
Airborne Laser Swath Mapping: Quantifying changes in sandy beaches over time scales of weeks to years,
PandRS(59), No. 4, June 2005, pp. 222-232.
Elsevier DOI 0509
BibRef

Gressin, A.[Adrien], Mallet, C.[Clément], Demantké, J.[Jérôme], David, N.[Nicolas],
Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge,
PandRS(79), No. 1, May 2013, pp. 240-251.
Elsevier DOI 1305
BibRef
Earlier: A1, A2, A4, Only:
Improving 3D Lidar Point Cloud Registration Using Optimal Neighborhood Knowledge,
AnnalsPRS(I-3), No. 2012, pp. 111-116.
DOI Link 1209
Point cloud; Registration; ICP; Eigenvalues; Dimensionality; Neighborhood; Change detection BibRef

Gressin, A., Cannelle, B., Mallet, C., Papelard, J.P.,
Trajectory-based Registration of 3d Lidar Point Clouds Acquired With A Mobile Mapping System,
AnnalsPRS(I-3), No. 2012, pp. 117-122.
DOI Link 1209
BibRef

Williams, J.G.[Jack G.], Anders, K.[Katharina], Winiwarter, L.[Lukas], Zahs, V.[Vivien], Höfle, B.[Bernhard],
Multi-directional change detection between point clouds,
PandRS(172), 2021, pp. 95-113.
Elsevier DOI 2101
Point cloud, LiDAR, 3D change detection, M3C2, Cloud-to-cloud comparison BibRef

Anders, K.[Katharina], Winiwarter, L.[Lukas], Mara, H.[Hubert], Lindenbergh, R.[Roderik], Vos, S.E.[Sander E.], Höfle, B.[Bernhard],
Fully automatic spatiotemporal segmentation of 3D LiDAR time series for the extraction of natural surface changes,
PandRS(173), 2021, pp. 297-308.
Elsevier DOI 2102
4D object-by-change, Point clouds, Terrestrial laser scanning, Change detection, Coastal monitoring BibRef

de Gélis, I.[Iris], Lefèvre, S.[Sébastien], Corpetti, T.[Thomas],
Change Detection in Urban Point Clouds: An Experimental Comparison with Simulated 3D Datasets,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Bailey, G.[Gene], Li, Y.K.[Ying-Kui], McKinney, N.[Nathan], Yoder, D.[Daniel], Wright, W.[Wesley], Washington-Allen, R.A.[Robert A.],
Las2DoD: Change Detection Based on Digital Elevation Models Derived from Dense Point Clouds with Spatially Varied Uncertainty,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Jaskulski, M.[Marcin], Jazdzewska, I.[Iwona], Szmidt, A.[Aleksander],
Changes in Land Relief in Urbanised Areas Using Laser Scanning and Archival Data on the Example of (Poland),
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

de Gélis, I.[Iris], Lefèvre, S.[Sébastien], Corpetti, T.[Thomas],
DC3DCD: Unsupervised learning for multiclass 3D point cloud change detection,
PandRS(206), 2023, pp. 168-183.
Elsevier DOI Code:
WWW Link. 2312
3D point clouds, Change detection, Unsupervised deep learning, Deep clustering BibRef

Stilla, U.[Uwe], Xu, Y.S.[Yu-Sheng],
Change detection of urban objects using 3D point clouds: A review,
PandRS(197), 2023, pp. 228-255.
Elsevier DOI 2303
Change detection, Point clouds, Urban objects, Applications BibRef

de Gélis, I.[Iris], Lefèvre, S.[Sébastien], Corpetti, T.[Thomas],
Siamese KPConv: 3D multiple change detection from raw point clouds using deep learning,
PandRS(197), 2023, pp. 274-291.
Elsevier DOI 2303
3D point clouds, Change detection, Deep learning, Siamese network, 3D Kernel Point Convolution BibRef

Casas-Rosa, J.C.[Juan C.], Navarro, P.[Pablo], Segura-Sánchez, R.J.[Rafael J.], Rueda-Ruiz, A.J.[Antonio J.], López-Ruiz, A.[Alfonso], Fuertes, J.M.[José M.], Delrieux, C.[Claudio], Ogayar-Anguita, C.J.[Carlos J.],
Change Detection in Point Clouds Using 3D Fractal Dimension,
RS(16), No. 6, 2024, pp. 1054.
DOI Link 2403
BibRef


Naylor, P.[Peter], di Carlo, D.[Diego], Traviglia, A.[Arianna], Yamada, M.[Makoto], Fiorucci, M.[Marco],
Implicit neural representation for change detection,
WACV24(924-934)
IEEE DOI 2404
Point cloud compression, Surface reconstruction, Laser radar, Shape, Noise, Urban planning, Algorithms, Remote Sensing BibRef

Fuse, T., Yamano, T.,
Change Detection of Time-series 3d Point Clouds Using Robust Principal Component Analysis,
ISPRS21(B2-2021: 163-169).
DOI Link 2201
BibRef

Vaiapury, K.[Karthikeyan], Purushothaman, B.[Balamuralidhar], Pal, A.[Arpan], Agarwal, S.[Swapna],
Can We Speed up 3D Scanning? A Cognitive and Geometric Analysis,
CogCV17(2690-2696)
IEEE DOI 1802
Change detection in 3D point clouds. Aircraft, Atmospheric modeling, Automobiles, Force, Shape, Strain, BibRef

Al-Rawabdeh, A., Al-Gurrani, H., Al-Durgham, K., Detchev, I., He, F., El-Sheimy, N., Habib, A.,
A Robust Registration Algorithm For Point Clouds From UAV Images For Change Detection,
ISPRS16(B1: 765-772).
DOI Link 1610
BibRef

Pollard, T.[Thomas], Mundy, J.L.[Joseph L.],
Change Detection in a 3-d World,
CVPR07(1-6).
IEEE DOI 0706
BibRef

Girardeau-Montaut, D., Roux, M., Marc, R., Thibault, G.,
Change detection on point cloud data acquired with a ground laser scanner,
Laser05(xx-yy).
PDF File. 0509
BibRef

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Register 3-D Surfaces, Mesh Models .


Last update:May 6, 2024 at 15:50:14