12.3.4.1.12 Image to 3-D Surface Matching, 2-D to 3-D Matching, 2-D to 3-D Registration

Chapter Contents (Back)
Matching, Surfaces. Surface Matching. 2D-3D Matching. 3D-2D, 2D-3D, 2D/3D
See also Fusion, Range or Depth and Intensity or Color Data.

Horn, B.K.P., and Bachman, B.L.[Brett L.],
Using Synthetic Images to Register Real Surfaces with Surface Models,
CACM(21), No. 11, November 1978, pp. 914-924. BibRef 7811
Earlier: DARPAO77(75-95). BibRef
Earlier: MIT AI Memo- 437, August 1977. Matching is easy, realistic shading is the goal. BibRef

Horn, B.K.P., and Bachman, B.L.[Brett L.],
Registering Real Images Using Synthetic Images,
AI-MIT79(129-159). BibRef 7900

Viola, P.A.[Paul A.], Wells, III, W.M.[William M.],
Alignment by Maximization of Mutual Information,
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DOI Link 9710

PS File. BibRef
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Earlier: A1 only: MIT AI-TR-1548, March 1995. BibRef Ph.D.Thesis, MIT, 1995.
WWW Link. Or:
PS File. When standard assumptions fail (lighting). The idea is that 2 points that are similar in the model should be similar in the image (i.e. similar surface orientations lead to similar pixel values). A similar formulation could be arrived at through a maximum likelihood approach. BibRef

Wells, III, W.M., Halle, M., Kikinis, R., Viola, P.A.,
Alignment and Tracking Using Graphics Hardware,
ARPA96(837-842). BibRef 9600

Viola, P.A.[Paul A.],
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Guest, E.[Elizabeth], Berry, E.[Elizabeth], Baldock, R.A.[Richard A.], Fidrich, M.[Marta], Smith, M.A.[Mike A.],
Robust Point Correspondence Applied to Two- and Three-Dimensional Image Registration,
PAMI(23), No. 2, February 2001, pp. 165-179.
IEEE DOI 0102
Medical problems. Based on sensitivity to movement, if a point moves there should not be a large change in the correspondence. BibRef

Guest, E., Berry, E., Morris, D.,
Using the CSM Correspondence Calculation Algorithm to Quantify Differences between Surfaces,
BMVC00(xx-yy).
PDF File. 0009
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Guest, E., Fidrich, M., Kelly, S., Berry, E.,
Robust surface matching for registration,
3DIM99(169-177).
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Clarkson, M.J.[Matthew J.], Rueckert, D.[Daniel], Hill, D.L.G.[Derek L.G.], Hawkes, D.J.[David J.],
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PAMI(23), No. 11, November 2001, pp. 1266-1280.
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Face Recognition. How consistent the optical image in each view is with the lighting model. Apply to face images. BibRef

Cahill, N.D.[Nathan D.],
Normalized Measures of Mutual Information with General Definitions of Entropy for Multimodal Image Registration,
WBIR10(258-268).
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Lee, D.W.[Dae-Won], Hofmann, M.[Matthias], Steinke, F.[Florian], Altun, Y.[Yasemin], Cahill, N.D.[Nathan D.], Scholkopf, B.[Bernhard],
Learning similarity measure for multi-modal 3D image registration,
CVPR09(186-193).
IEEE DOI 0906
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Cahill, N.D.[Nathan D.], Noble, J.A.[J. Alison], Hawkes, D.J.[David J.],
Fourier Methods for Nonparametric Image Registration,
Fusion07(1-8).
IEEE DOI 0706
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Shan, J.[Jie], Yoon, J.S.[Jong-Suk], Lee, D.S.[D. Scott], Kirk, R.L.[Randolph L.], Neumann, G.A.[Gregory A.], Acton, C.H.[Charles H.],
Photogrammetric Analysis of the Mars Global Surveyor Mapping Data,
PhEngRS(71), No. 1, January 2005, pp. 97. Mars Orbiter Laser Altimeter (MOLA) Profiles are registered with stereo Mars Orbiter Camera images at a nearly constant uncertainty of one MOLA ground spacing distance along the flight direction.
WWW Link. 0509
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Habib, A.[Ayman], Ghanma, M.[Mwafag], Morgan, M.[Michel], Al-Ruzouq, R.[Rami],
Photogrammetric and Lidar Data Registration Using Linear Features,
PhEngRS(71), No. 6, June 2005, pp. 699-708. Different methodologies for registering photogrammetric and lidar datasets to a common reference frame using straight lines.
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Aouadi, S.[Souha], Sarry, L.[Laurent],
Accurate and precise 2D-3D registration based on X-ray intensity,
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Earlier:
An Accurate Mutual Information-based Registration of Digitized,
WACV07(54-54).
IEEE DOI 0702
2D-3D registration; Object pose; Mutual information; Digital radiography; Computed tomography; Stochastic clustering 3D pose from digitized X-Ray data. BibRef

Fleck, S.[Sven], Busch, F.[Florian], Biber, P.[Peter], Strasser, W.[Wolfgang],
Graph Cut based Panoramic 3D Modeling and Ground Truth Comparison with a Mobile Platform: The Wagele,
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Earlier: CRV06(19-19).
IEEE DOI 0607
Graph cut; 3D model acquisition; 3DTV BibRef

Biber, P.[Peter], Fleck, S.[Sven], Duckett, T.,
3D Modeling of Indoor Environments for a Robotic Security Guard,
SafeSecur05(III: 124-124).
IEEE DOI 0507
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Biber, P.[Peter], Fleck, S.[Sven], Strasser, W.[Wolfgang],
A Probabilistic Framework for Robust and Accurate Matching of Point Clouds,
DAGM04(480-487).
Springer DOI 0505
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Wong, A., Orchard, J.,
Efficient FFT-Accelerated Approach to Invariant Optical-LIDAR Registration,
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IEEE DOI 0812
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González Aguilera, D.[Diego], Rodríguez Gonzálvez, P.[Pablo], Gómez Lahoz, J.[Javier],
An automatic procedure for co-registration of terrestrial laser scanners and digital cameras,
PandRS(64), No. 3, May 2009, pp. 308-316.
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Earlier:
Automatic Co-Registration of Terrestrial Laser Scanner and Digital Camera for the Generation of Hybrids Models,
Laser07(162).
PDF File. 0709
Image analysis; Laserscanning; Close-range photogrammetry; Sensor fusion; Software development BibRef

Groher, M., Zikic, D., Navab, N.,
Deformable 2D-3D Registration of Vascular Structures in a One View Scenario,
MedImg(28), No. 6, June 2009, pp. 847-860.
IEEE DOI 0906
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Zikic, D.[Darko], Kamen, A.[Ali], Navab, N.[Nassir],
Natural gradients for deformable registration,
CVPR10(2847-2854).
IEEE DOI 1006
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Zikic, D.[Darko], Baust, M.[Maximilian], Kamen, A.[Ali], Navab, N.[Nassir],
A general preconditioning scheme for difference measures in deformable registration,
ICCV11(49-56).
IEEE DOI 1201
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Groher, M.[Martin], Baust, M.[Maximilian], Zikic, D.[Darko], Navab, N.[Nassir],
Monocular Deformable Model-to-Image Registration of Vascular Structures,
WBIR10(37-47).
Springer DOI 1007
BibRef

Detry, R.[Renaud], Pugeault, N.[Nicolas], Piater, J.H.[Justus H.],
A Probabilistic Framework for 3D Visual Object Representation,
PAMI(31), No. 10, October 2009, pp. 1790-1803.
IEEE DOI 0909
BibRef
Earlier:
Probabilistic Pose Recovery Using Learned Hierarchical Object Models,
CogVis08(107-120).
Springer DOI 0805
3D features and probabilitistic relations. BibRef

Detry, R.[Renaud], Piater, J.H.[Justus H.],
Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition,
ACCV10(III: 572-585).
Springer DOI 1011
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Teney, D.[Damien], Piater, J.H.[Justus H.],
Multiview feature distributions for object detection and continuous pose estimation,
CVIU(125), No. 1, 2014, pp. 265-282.
Elsevier DOI 1406
BibRef
Earlier:
Continuous Pose Estimation in 2D Images at Instance and Category Levels,
CRV13(121-127)
IEEE DOI 1308
BibRef
And:
Modeling Pose/Appearance Relations for Improved Object Localization and Pose Estimation in 2D images,
IbPRIA13(59-68).
Springer DOI 1307
BibRef
Earlier:
Generalized Exemplar-Based Full Pose Estimation from 2D Images without Correspondences,
DICTA12(1-8).
IEEE DOI 1303
BibRef
Earlier:
Probabilistic Object Models for Pose Estimation in 2D Images,
DAGM11(336-345).
Springer DOI 1109
Appearance-based object recognition. Approximation methods BibRef

Xiong, H.C.[Han-Chen], Szedmak, S.[Sandor], Piater, J.H.[Justus H.],
A Study of Point Cloud Registration with Probability Product Kernel Functions,
3DV13(207-214)
IEEE DOI 1311
BibRef
And:
Efficient, General Point Cloud Registration with Kernel Feature Maps,
CRV13(83-90)
IEEE DOI 1308
Gaussian processes. Computational modeling BibRef

Simonsen, K.B.[Kasper Broegaard], Nielsen, M.T.[Mads Thorsted], Pilz, F.[Florian], Krüger, N.[Norbert], Pugeault, N.[Nicolas],
Spatial-Temporal Junction Extraction and Semantic Interpretation,
ISVC09(I: 275-286).
Springer DOI 0911
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Jensen, L.B.W.[Lars B. W.], Baseski, E.[Emre], Kalkan, S.[Sinan], Pugeault, N.[Nicolas], Wörgötter, F.[Florentin], Krüger, N.[Norbert],
Semantic Reasoning for Scene Interpretation,
CogVis08(121-134).
Springer DOI 0805
Representation by labelled graphs. BibRef

Pilz, F.[Florian], Shi, Y.[Yan], Grest, D.[Daniel], Pugeault, N.[Nicolas], Kalkan, S.[Sinan], Krüger, N.[Norbert],
Utilizing Semantic Interpretation of Junctions for 3D-2D Pose Estimation,
ISVC07(I: 692-701).
Springer DOI 0711

See also Scene Representation Based on Multi-Modal 2D and 3D Features, A. BibRef

Wang, M.[Mi], Hu, F.[Fen], Li, J.[Jonathan], Pan, J.[Jun],
A Fast Approach to Best Scanline Search of Airborne Linear Pushbroom Images,
PhEngRS(75), No. 9, September 2009, pp. 1059-1068.
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Wang, M.[Mi], Hu, F.[Fen],
A Fast Object-to-Image Best Scanline Search Algorithm for Airborne Linear Pushbroom Image Processing,
ISPRS08(B3b: 73 ff).
PDF File. 0807
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Pati, U.C.[Umesh C.], Dutta, P.K.[Pranab K.], Barua, A.[Alok],
Feature level fusion of range and intensity images of an object,
IJCVR(1), No. 1, 2009, pp. 2-33.
DOI Link 0911
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Palenichka, R.M.[Roman M.], Zaremba, M.B.[Marek B.],
Automatic Extraction of Control Points for the Registration of Optical Satellite and LiDAR Images,
GeoRS(48), No. 7, July 2010, pp. 2864-2879.
IEEE DOI 1007
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Earlier:
A Spatio-Temporal Isotropic Operator for the Attention-Point Extraction,
CAIP09(318-325).
Springer DOI 0909

See also Fast Structure-Adaptive Evaluation of Local Features in Images, A.
See also Multiscale Isotropic Matched Filtering for Individual Tree Detection in LiDAR Images.
See also fast algorithm for the computation of axial moments and its application to the orthogonal fitting of curves, A. BibRef

Sandhu, R.[Romeil], Dambreville, S.[Samuel], Tannenbaum, A.[Allen],
Point Set Registration via Particle Filtering and Stochastic Dynamics,
PAMI(32), No. 8, August 2010, pp. 1459-1473.
IEEE DOI 1007
BibRef
Earlier:
Particle filtering for registration of 2D and 3D point sets with stochastic dynamics,
CVPR08(1-8).
IEEE DOI 0806
Rigid body transformation. BibRef

Sandhu, R.[Romeil], Dambreville, S.[Samuel], Yezzi, A.J.[Anthony J.], Tannenbaum, A.[Allen],
A Nonrigid Kernel-Based Framework for 2D-3D Pose Estimation and 2D Image Segmentation,
PAMI(33), No. 6, June 2011, pp. 1098-1115.
IEEE DOI 1105
BibRef
Earlier:
Non-rigid 2D-3D pose estimation and 2D image segmentation,
CVPR09(786-793).
IEEE DOI 0906

See also Particle filters and occlusion handling for rigid 2D-3D pose tracking. BibRef

Tsukada, M.[Masahiro], Utsumi, Y.[Yuya], Madokoro, H.[Hirokazu], Sato, K.[Kazuhito],
Unsupervised Feature Selection and Category Classification for a Vision-Based Mobile Robot,
IEICE(E94-D), No. 1, January 2011, pp. 127-136.
WWW Link. 1101
Selection of feature points. Detection, Selection, Descriptors, labels, categories. BibRef

Madokoro, H.[Hirokazu], Tsukada, M.[Masahiro], Sato, K.[Kazuhito],
Unsupervised Feature Selection and Category Formation for Generic Object Recognition,
CAIP11(I: 427-434).
Springer DOI 1109
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Damas, S.[Sergio], Cordón, O.[Oscar], Ibáńez, O.[Oscar], Santamaría, J.[Jose], Alemán, I.[Inmaculada], Botella, M.[Miguel], Navarro, F.[Fernando],
Forensic identification by computer-aided craniofacial superimposition: A survey,
Surveys(43), No. 4, October 2011, pp. xx-yy.
DOI Link 1110
Survey, Alignment. Craniofacial superimposition is a forensic process in which a photograph of a missing person is compared with a skull found to determine its identity. After one century of development, craniofacial superimposition has become an interdisciplinary research BibRef

Leng, D.W., Sun, W.D.,
Contour-based iterative pose estimation of 3D rigid object,
IET-CV(5), No. 5, 2011, pp. 291-300.
DOI Link 1110
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Leng, D.W., Sun, W.D.,
Iterative three-dimensional rigid object pose estimation with contour correspondence,
IET-IPR(6), No. 5, 2012, pp. 569-579.
DOI Link 1210
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Liu, C.[Ce], Yuen, J.[Jenny], Torralba, A.B.[Antonio B.],
Nonparametric Scene Parsing via Label Transfer,
PAMI(33), No. 12, December 2011, pp. 2368-2382.
IEEE DOI 1110
BibRef
Earlier:
Nonparametric scene parsing: Label transfer via dense scene alignment,
CVPR09(1972-1979).
IEEE DOI 0906
Award, CVPR, Student. Best alignment of image with database for recognition. Recognition by matching with labeled database rather than by learning.
See also SIFT Flow: Dense Correspondence across Different Scenes. For a non-technical discussion of this method look at a news item on this technique BibRef

Lim, J.J.[Joseph J.], Pirsiavash, H.[Hamed], Torralba, A.B.[Antonio B.],
Parsing IKEA Objects: Fine Pose Estimation,
ICCV13(2992-2999)
IEEE DOI 1403
BibRef

Grant, D.[Darion], Bethel, J.[James], Crawford, M.[Melba],
Point-to-plane registration of terrestrial laser scans,
PandRS(72), No. 1, August 2012, pp. August 2012, 16-26.
Elsevier DOI 1209
BibRef
Earlier:
Rigorous Point-to-plane Registration of Terrestrial Laser Scans,
ISPRS12(XXXIX-B5:181-186).
DOI Link 1209
LIDAR; Point cloud; Terrestrial laser scanning; Surface registration BibRef

Dorgham, O.[Osama], Fisher, M.[Mark], Laycock, S.[Stephen],
Performance of a 2D-3D Image Registration System using (Lossy) Compressed X-ray CT,
BMVA(2009), No. 3, 2009, pp. 1-11.
PDF File. 1209
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Corsini, M., Dellepiane, M., Ganovelli, F., Gherardi, R., Fusiello, A., Scopigno, R.,
Fully Automatic Registration of Image Sets on Approximate Geometry,
IJCV(102), No. 1-3, March 2013, pp. 91-111.
Springer DOI 1303
Color images mapped onto 3D. BibRef

Bae, M.S.[Min Soo], Park, I.K.[In Kyu],
Content-based 3D model retrieval using a single depth image from a low-cost 3D camera,
VC(29), No. 6-8, June 2013, pp. 555-564.
Springer DOI 1306
For query. Use the depth image. BibRef

Chou, C.R.[Chen-Rui], Frederick, B.[Brandon], Mageras, G.[Gig], Chang, S.[Sha], Pizer, S.M.[Stephen M.],
2D/3D image registration using regression learning,
CVIU(117), No. 9, 2013, pp. 1095-1106.
Elsevier DOI 1307
2D/3D registration BibRef

Zhao, Q., Chou, C.R.[Chen-Rui], Mageras, G., Pizer, S.M.[Stephen M.],
Local Metric Learning in 2D/3D Deformable Registration With Application in the Abdomen,
MedImg(33), No. 8, August 2014, pp. 1592-1600.
IEEE DOI 1408
BibRef
Earlier: A2, A4, Only:
Local Regression Learning via Forest Classification for 2D/3D Deformable Registration,
MCV13(24-33).
Springer DOI 1405
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Earlier: A2, A4, Only:
Real-Time 2D/3D Deformable Registration Using Metric Learning,
MCVM12(1-10).
Springer DOI 1305
Computed tomography BibRef

Gomez, J.[Juan], Bologna, G.[Guido], Pun, T.[Thierry],
Efficient registering of color and range images,
JIVP(2013), No. 1, 2013, pp. 41.
DOI Link 1307
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Álvarez, H.[Hugo], Borro, D.[Diego],
Junction assisted 3D pose retrieval of untextured 3D models in monocular images,
CVIU(117), No. 10, 2013, pp. 1204-1214.
Elsevier DOI 1309
Computer vision
See also GFT: GPU Fast Triangulation of 3D Points. BibRef

Rouhani, M.[Mohammad], Sappa, A.D.[Angel Domingo],
The Richer Representation the Better Registration,
IP(22), No. 12, 2013, pp. 5036-5049.
IEEE DOI 1312
image registration BibRef

Rouhani, M.[Mohammad], Sappa, A.D.[Angel D.],
Non-rigid Shape Registration: A Single Linear Least Squares Framework,
ECCV12(VII: 264-277).
Springer DOI 1210
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Earlier:
Correspondence free registration through a point-to-model distance minimization,
ICCV11(2150-2157).
IEEE DOI 1201
Between points and model BibRef

Qin, R.J.[Rong-Jun], Gruen, A.[Armin],
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Qin, R.J.[Rong-Jun], Gruen, A.[Armin],
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PCV14(259-264).
DOI Link 1404
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Samir, C., Kurtek, S., Srivastava, A., Canis, M.,
Elastic Shape Analysis of Cylindrical Surfaces for 3D/2D Registration in Endometrial Tissue Characterization,
MedImg(33), No. 5, May 2014, pp. 1035-1043.
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Deformation BibRef

Wang, Y., Wang, R., Dai, Q.,
A Parametric Model for Describing the Correlation Between Single Color Images and Depth Maps,
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Color BibRef

Morago, B.[Brittany], Bui, G.[Giang], Duan, Y.[Ye],
An Ensemble Approach to Image Matching Using Contextual Features,
IP(24), No. 11, November 2015, pp. 4474-4487.
IEEE DOI 1509
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Earlier:
Integrating LIDAR Range Scans and Photographs with Temporal Changes,
FusionOutdoor14(732-737)
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2D-3D fusion BibRef

Morago, B., Bui, G.[Giang], Duan, Y.[Ye],
2D Matching Using Repetitive and Salient Features in Architectural Images,
IP(25), No. 10, October 2016, pp. 4888-4899.
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buildings (structures) BibRef

Avbelj, J.[Janja], Iwaszczuk, D.[Dorota], Müller, R.[Rupert], Reinartz, P.[Peter], Stilla, U.[Uwe],
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Line-Based Registration of DSM and Hyperspectral Images,
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DOI Link 1308
Hyper spectral BibRef

Iwaszczuk, D., Helmholz, P., Belton, D., Stilla, U.[Uwe],
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Satkin, S.[Scott], Rashid, M.[Maheen], Lin, J.[Jason], Hebert, M.[Martial],
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Relate an image to large collection of 3D models. BibRef

Rashid, M.[Maheen], Hebert, M.[Martial],
Detailed 3D Model Driven Single View Scene Understanding,
3DV14(139-146)
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Geometry BibRef

Hansard, M.[Miles], Evangelidis, G.D.[Georgios D.], Pelorson, Q.[Quentin], Horaud, R.[Radu],
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Abayowa, B.O.[Bernard O.], Yilmaz, A.[Alper], Hardie, R.C.[Russell C.],
Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models,
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Hosseinyalamdary, S., Yilmaz, A.,
Surface Recovery: Fusion of Image and Point Cloud,
MSF15(175-183)
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Lindner, C.[Claudia], Bromiley, P.A., Ionita, M.C.[Mircea C.], Cootes, T.F.[Tim F.],
Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting,
PAMI(37), No. 9, September 2015, pp. 1862-1874.
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Detectors BibRef

Cootes, T.F.[Tim F.], Ionita, M.C.[Mircea C.], Lindner, C.[Claudia], Sauer, P.[Patrick],
Robust and Accurate Shape Model Fitting Using Random Forest Regression Voting,
ECCV12(VII: 278-291).
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Wu, B.[Bo], Tang, S.J.[Sheng-Jun], Zhu, Q.[Qing], Tong, K.Y.[Kwan-Yuen], Hu, H.[Han], Li, G.Y.[Guo-Yuan],
Geometric integration of high-resolution satellite imagery and airborne LiDAR data for improved geopositioning accuracy in metropolitan areas,
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Elsevier DOI 1512
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Yang, J.[Jian], Jones, T.[Trevor], Caspersen, J.[John], He, Y.H.[Yu-Hong],
Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data,
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Ghosh, S.[Shatadal], Ray, R.[Ranjit], Vadali, S.R.K.[Siva Ram Krishna], Shome, S.N.[Sankar Nath], Nandy, S.[Sambhunath],
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Springer DOI 1602
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Liu, S.J.[Shi-Jie], Tong, X.H.[Xiao-Hua], Chen, J.[Jie], Liu, X.F.[Xiang-Feng], Sun, W.Z.[Wen-Zheng], Xie, H.[Huan], Chen, P.[Peng], Jin, Y.M.[Yan-Min], Ye, Z.[Zhen],
A Linear Feature-Based Approach for the Registration of Unmanned Aerial Vehicle Remotely-Sensed Images and Airborne LiDAR Data,
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Khoshelham, K.[Kourosh],
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PandRS(114), No. 1, 2016, pp. 78-91.
Elsevier DOI 1604
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Earlier:
Direct 6-DoF Pose Estimation from Point-Plane Correspondences,
DICTA15(1-6)
IEEE DOI 1603
Registration. convergence BibRef

Khoshelham, K., Gorte, B.,
Registering point clouds of polyhedral buildings to 2D maps,
3DARCH09(xx-yy).
PDF File. 0902
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Hexner, J.[Jonathan], Hagege, R.R.[Rami R.],
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IJCV(118), No. 1, June 2016, pp. 95-112.
Springer DOI 1605
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Miao, S., Wang, Z.J., Liao, R.,
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IEEE DOI 1605
Attenuation BibRef

Aldoma, A.[Aitor], Tombari, F.[Federico], di Stefano, L.[Luigi], Vincze, M.[Markus],
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PAMI(38), No. 7, July 2016, pp. 1383-1396.
IEEE DOI 1606
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Earlier:
A Global Hypotheses Verification Method for 3D Object Recognition,
ECCV12(III: 511-524).
Springer DOI 1210
Clutter BibRef

Petrelli, A.[Alioscia], di Stefano, L.[Luigi],
A Repeatable and Efficient Canonical Reference for Surface Matching,
3DIMPVT12(403-410).
IEEE DOI 1212
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Khoo, Y., Kapoor, A.,
Non-Iterative Rigid 2D/3D Point-Set Registration Using Semidefinite Programming,
IP(25), No. 7, July 2016, pp. 2956-2970.
IEEE DOI 1606
computer vision BibRef

Zhou, G.Q.[Guo-Qing], Luo, Q.L.[Qing-Li], Xie, W.H.[Wen-Han], Yue, T.[Tao], Huang, J.J.[Jing-Jin], Shen, Y.Z.[Yu-Zhong],
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RS(8), No. 6, 2016, pp. 507.
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Semantic annotation for complex video street views based on 2D-3D multi-feature fusion and aggregated boosting decision forests,
PR(62), No. 1, 2017, pp. 189-201.
Elsevier DOI 1705
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Yu, W.M.[Wei-Min], Tannast, M.[Moritz], Zheng, G.[Guoyan],
Non-rigid free-form 2D-3D registration using a B-spline-based statistical deformation model,
PR(63), No. 1, 2017, pp. 689-699.
Elsevier DOI 1612
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Earlier: A3, A1, Only:
Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model,
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Springer DOI 1511
Free-from deformation BibRef

Li, F.[Fei], Du, Y.[Yunfan], Liu, R.J.[Ru-Jie],
Color-Introduced Frame-to-Model Registration for 3D Reconstruction,
MMMod17(II: 112-123).
Springer DOI 1701
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Phan, M.S.[Minh Son], Baudrier, É.[Étienne], Mazo, L.[Loďc], Tajine, M.[Mohamed],
Moment-Based Angular Difference Estimation Between Two Tomographic Projections in 2D and 3D,
JMIV(57), No. 2, February 2017, pp. 164-182.
Springer DOI 1702
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Zhao, H.J.[Hui-Jie], Shi, S.G.[Shao-Guang], Gu, X.F.[Xing-Fa], Jia, G.R.[Guo-Rui], Xu, L.[Lunbao],
Integrated System for Auto-Registered Hyperspectral and 3D Structure Measurement at the Point Scale,
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de Silva, T., Cool, D.W., Yuan, J., Romagnoli, C., Samarabandu, J., Fenster, A., Ward, A.D.,
Robust 2-D-3-D Registration Optimization for Motion Compensation During 3-D TRUS-Guided Biopsy Using Learned Prostate Motion Data,
MedImg(36), No. 10, October 2017, pp. 2010-2020.
IEEE DOI 1710
Biopsy, Cancer, Probes, Robustness, Ultrasonic imaging, 2D-3D registration, motion compensation, prostate biopsy, registration optimization, ultrasound, guidance BibRef

Plötz, T.[Tobias], Roth, S.[Stefan],
Automatic Registration of Images to Untextured Geometry Using Average Shading Gradients,
IJCV(125), No. 1-3, December 2018, pp. 65-81.
Springer DOI 1711
BibRef
Earlier:
Registering Images to Untextured Geometry Using Average Shading Gradients,
ICCV15(2030-2038)
IEEE DOI 1602
Registering photos with no texture information. Cameras BibRef

Gao, M.L.[Mao-Lin], Lähner, Z.[Zorah], Thunberg, J.[Johan], Cremers, D.[Daniel], Bernard, F.[Florian],
Isometric Multi-Shape Matching,
CVPR21(14178-14188)
IEEE DOI 2111
Shape, Linear programming, Complexity theory, Object tracking, Optimization BibRef

Bernard, F.[Florian], Schmidt, F.R., Thunberg, J.[Johan], Cremers, D.[Daniel],
A Combinatorial Solution to Non-Rigid 3D Shape-to-Image Matching,
CVPR17(1436-1445)
IEEE DOI 1711
Computational modeling, Labeling, Optimization, Shape, BibRef

Famouri, M.[Mahmoud], Bartoli, A.E.[Adrien E.], Azimifar, Z.[Zohreh],
Fast shape-from-template using local features,
MVA(29), No. 1, January 2018, pp. 73-93.
Springer DOI 1801
3D from 1 image. Reconstruct give a 3D template. BibRef

Li, F.[Fei], Du, Y.F.[Yun-Fan], Tian, H.[Hu], Liu, R.J.[Ru-Jie],
Color Mapping for 3D Geometric Models without Reference Image Locations,
DICTA17(1-6)
IEEE DOI 1804
cameras, image colour analysis, image reconstruction, image registration, pose estimation, BibRef

Li, W.[Wen], Chen, L.[Lin], Xu, D.[Dong], Van Gool, L.J.[Luc J.],
Visual Recognition in RGB Images and Videos by Learning from RGB-D Data,
PAMI(40), No. 8, August 2018, pp. 2030-2036.
IEEE DOI 1807
BibRef
Earlier: A2, A1, A3, Only:
Recognizing RGB Images by Learning from RGB-D Data,
CVPR14(1418-1425)
IEEE DOI 1409
Feature extraction, Image recognition, Testing, Training, Training data, Videos, Visualization, Domain adaptation, object recognition. RGB-D examples, RGB images as input. BibRef

Gómez, O.[Oscar], Ibáńez, O.[Oscar], Valsecchi, A.[Andrea], Cordón, O.[Oscar], Kahana, T.[Tzipi],
3D-2D silhouette-based image registration for comparative radiography-based forensic identification,
PR(83), 2018, pp. 469-480.
Elsevier DOI 1808
Forensic identification, Comparative radiography, 3D-2D image registration, Evolutionary computation BibRef

Usamentiaga, R.[Rubén], García, D.F.[Daniel F.], Molleda, J.[Julio],
Efficient registration of 2D points to CAD models for real-time applications,
RealTimeIP(15), No. 2, August 2018, pp. 329-347.
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Xin, X.[Xin], Liu, B.[Bin], Di, K.C.[Kai-Chang], Jia, M.[Mengna], Oberst, J.[Jürgen],
High-precision co-registration of orbiter imagery and digital elevation model constrained by both geometric and photometric information,
PandRS(144), 2018, pp. 28-37.
Elsevier DOI 1809
Co-registration, Geometric model, Photometric model, LRO NAC image, SLDEM2015, Lunar mapping BibRef

Paudel, D.P.[Danda Pani], Habed, A.[Adlane], Demonceaux, C.[Cédric], Vasseur, P.[Pascal],
Robust and Optimal Registration of Image Sets and Structured Scenes via Sum-of-Squares Polynomials,
IJCV(127), No. 5, May 2019, pp. 415-436.
Springer DOI 1903
BibRef
Earlier:
Robust and Optimal Sum-of-Squares-Based Point-to-Plane Registration of Image Sets and Structured Scenes,
ICCV15(2048-2056)
IEEE DOI 1602
BibRef
And:
LMI-based 2D-3D registration: From uncalibrated images to Euclidean scene,
CVPR15(4494-4502)
IEEE DOI 1510
BibRef
Earlier: A1, A3, A2, A4:
Localization of 2D Cameras in a Known Environment Using Direct 2D-3D Registration,
ICPR14(196-201)
IEEE DOI 1412
Barium BibRef

Van Gool, L.J.[Luc J.], Paudel, D.P.[Danda Pani], Habed, A.[Adlane],
Optimal Transformation Estimation with Semantic Cues,
ICCV17(4668-4677)
IEEE DOI 1802
computational geometry, image registration, image segmentation, linear matrix inequalities, search problems, 2D homography, BibRef

Liu, Y., Dong, Y., Song, Z., Wang, M.,
2D-3D Point Set Registration Based on Global Rotation Search,
IP(28), No. 5, May 2019, pp. 2599-2613.
IEEE DOI 1903
Search problems, Linear programming, Solid modeling, Cameras, global rotation search BibRef

Brown, M.[Mark], Windridge, D.[David], Guillemaut, J.Y.[Jean-Yves],
A family of globally optimal branch-and-bound algorithms for 2D-3D correspondence-free registration,
PR(93), 2019, pp. 36-54.
Elsevier DOI 1906
2D-3D registration, Multi-modal registration, Branch-and-bound, Global optimisation BibRef

Rashwan, H.A., Chambon, S., Gurdjos, P., Morin, G., Charvillat, V.,
Using Curvilinear Features in Focus for Registering a Single Image to a 3D Object,
IP(28), No. 9, Sep. 2019, pp. 4429-4443.
IEEE DOI 1908
feature extraction, image matching, image registration, photography, pose estimation, rendering (computer graphics), curvilinear saliency BibRef

Liu, W.Q.[Wei-Quan], Wang, C.[Cheng], Bian, X.S.[Xue-Sheng], Chen, S.T.[Shu-Ting], Li, W.[Wei], Lin, X.H.[Xiu-Hong], Li, Y.C.[Yong-Chuan], Weng, D.D.[Dong-Dong], Lai, S.H.[Shang-Hong], Li, J.[Jonathan],
AE-GAN-Net: Learning Invariant Feature Descriptor to Match Ground Camera Images and a Large-Scale 3D Image-Based Point Cloud for Outdoor Augmented Reality,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
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Zhou, Y.Q.[Ya-Qian], Liu, Y.[Yu], Zhou, H.[Heyu], Li, W.H.[Wen-Hui],
Wasserstein distance feature alignment learning for 2D image-based 3D model retrieval,
JVCIR(79), 2021, pp. 103197.
Elsevier DOI 2109
3D model retrieval, Multi-view learning, Cross-domain retrieval BibRef

Liu, Z.Z.[Zheng-Zhe], Qi, X.J.[Xiao-Juan], Fu, C.W.[Chi-Wing],
3D-to-2D Distillation for Indoor Scene Parsing,
CVPR21(4462-4472)
IEEE DOI 2111
Training, Knowledge engineering, Solid modeling, Semantics, Statistical distributions, Feature extraction BibRef

Liu, D.X.[Dong-Xu], Han, G.L.[Guang-Liang], Liu, P.X.[Pei-Xun], Yang, H.[Hang], Sun, X.L.[Xing-Long], Li, Q.Q.[Qing-Qing], Wu, J.J.[Jia-Jia],
A Novel 2D-3D CNN with Spectral-Spatial Multi-Scale Feature Fusion for Hyperspectral Image Classification,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
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Chang, X.[Xing], Yang, G.Q.[Gui-Qin], Chen, J.[Jiayu], Wang, X.P.[Xiao-Peng], Jiang, Z.J.[Zhan-Jun],
Spaceborne pose determination based on image to 3D digital surface model matching,
IET-IPR(16), No. 12, 2022, pp. 3314-3324.
DOI Link 2209
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Zhou, Y.Q.[Ya-Qian], Liu, Y.[Yu], Zhou, H.[Heyu], Cheng, Z.Y.[Zhi-Yong], Li, X.Y.[Xuan-Ya], Liu, A.A.[An-An],
Learning Transferable and Discriminative Representations for 2D Image-Based 3D Model Retrieval,
CirSysVideo(32), No. 10, October 2022, pp. 7147-7159.
IEEE DOI 2210
Solid modeling, Adaptation models, Feature extraction, Error analysis, Data models, Generative adversarial networks, multi-view BibRef

Wang, X.H.[Xuan-Han], Gao, L.L.[Lian-Li], Zhou, Y.X.[Yi-Xuan], Song, J.K.[Jing-Kuan], Wang, M.[Meng],
KTN: Knowledge Transfer Network for Learning Multiperson 2D-3D Correspondences,
CirSysVideo(32), No. 11, November 2022, pp. 7732-7745.
IEEE DOI 2211
Estimation, Annotations, Feature extraction, Training, Task analysis, Pipelines, Human densepose estimation, commonsense knowledge transfer BibRef

Zhao, C.H.[Chun-Hui], Wang, W.X.[Wen-Xuan], Yan, Y.M.[Yi-Ming], Su, N.[Nan], Feng, S.[Shou], Hou, W.[Wei], Xia, Q.Y.[Qing-Yu],
A Novel Object-Level Building-Matching Method across 2D Images and 3D Point Clouds Based on the Signed Distance Descriptor (SDD),
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
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Gao, C.[Cong], Feng, A.[Anqi], Liu, X.T.[Xing-Tong], Taylor, R.H.[Russell H.], Armand, M.[Mehran], Unberath, M.[Mathias],
A Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers,
MedImg(43), No. 1, January 2024, pp. 275-285.
IEEE DOI Code:
WWW Link. 2401
BibRef

Tang, S.J.[Sheng-Jun], Li, Y.[Yusong], Wan, J.W.[Jia-Wei], Li, Y.[You], Zhou, B.[Baoding], Guo, R.Z.[Ren-Zhong], Wang, W.X.[Wei-Xi], Feng, Y.H.[Yu-Hong],
TransCNNLoc: End-to-end pixel-level learning for 2D-to-3D pose estimation in dynamic indoor scenes,
PandRS(207), 2024, pp. 218-230.
Elsevier DOI 2401
Indoor localization, Feature learning, Structure from motion, Levenberg-Marquardt, Image retrieval BibRef


Roetzer, P.[Paul], Lähner, Z.[Zorah], Bernard, F.[Florian],
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching,
CVPR23(21866-21875)
IEEE DOI 2309
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Jaganathan, S.[Srikrishna], Kukla, M.[Maximilian], Wang, J.[Jian], Shetty, K.[Karthik], Maier, A.[Andreas],
Self-Supervised 2D/3D Registration for X-Ray to CT Image Fusion,
WACV23(2787-2797)
IEEE DOI 2302
Training, Representation learning, Deep learning, Computed tomography, Neural networks, Self-supervised learning BibRef

Janik, M.[Maciej], Gard, N.[Niklas], Hilsmann, A.[Anna], Eisert, P.[Peter],
Zero in on Shape: A Generic 2D-3D Instance Similarity Metric Learned from Synthetic Data,
ICIP21(2638-2642)
IEEE DOI 2201
Training, Measurement, Solid modeling, Shape, Training data, Network architecture, 3D model retrieval, zero-shot, domain gap BibRef

Rajamohan, D.[Deepak], Garratt, M.[Matthew], Pickering, M.R.[Mark R.],
A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model,
DICTA20(1-7)
IEEE DOI 2201
Solid modeling, Structure from motion, Surveillance, Cameras, Trajectory BibRef

Tang, H., Hsung, T.C., Lam, W.Y.H., Cheng, L.Y.Y., Pow, E.H.N.,
On 2D-3D Image Feature Detections for Image-To-Geometry Registration in Virtual Dental Model,
VCIP20(140-143)
IEEE DOI 2102
Teeth, Image color analysis, Dentistry, Surface morphology, Range Image BibRef

Zhang, S., Lichti, D.D., Küpper, J.C., Ronsky, J.L.,
An Automatic ICP-based 2d-3d Registration Method for A High-speed Biplanar Videoradiography Imaging System,
ISPRS20(B2:805-812).
DOI Link 2012
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Sundermeyer, M.[Martin], Durner, M.[Maximilian], Puang, E.Y.[En Yen], Marton, Z.C.[Zoltan-Csaba], Vaskevicius, N.[Narunas], Arras, K.O.[Kai O.], Triebel, R.[Rudolph],
Multi-Path Learning for Object Pose Estimation Across Domains,
CVPR20(13913-13922)
IEEE DOI 2008
Training, Encoding, Feature extraction, Decoding, Pose estimation, Solid modeling BibRef

Lange, A.[Annkristin], Heldmann, S.[Stefan],
Multilevel 2d-3d Intensity-based Image Registration,
WBIR20(57-66).
Springer DOI 2006
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Georgakis, G., Karanam, S., Wu, Z., Kosecka, J.,
Learning Local RGB-to-CAD Correspondences for Object Pose Estimation,
ICCV19(8966-8975)
IEEE DOI 2004
CAD, computational geometry, feature extraction, image colour analysis, image matching, image registration, Shape BibRef

Reddy, N.D.[N. Dinesh], Vo, M.[Minh], Narasimhan, S.G.[Srinivasa G.],
Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks,
CVPR19(7318-7327).
IEEE DOI 2002
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Liao, H.[Haofu], Lin, W.A.[Wei-An], Zhang, J.R.[Jia-Rui], Zhang, J.D.[Jing-Dan], Luo, J.B.[Jie-Bo], Zhou, S.K.[S. Kevin],
Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation,
CVPR19(12630-12639).
IEEE DOI 2002
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Semler, Q., Suwardhi, D., Alby, E., Murtiyoso, A., Macher, H.,
Registration of 2d Drawings On a 3d Point Cloud As a Support for The Modeling of Complex Architectures,
CIPA19(1083-1087).
DOI Link 1912
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Schmitz, S., Weinmann, M., Ruf, B.,
Automatic Co-registration of Aerial Imagery and Untextured Model Data Utilizing Average Shading Gradients,
UAV-g19(581-588).
DOI Link 1912
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Milz, S.[Stefan], Simon, M.[Martin], Fischer, K.[Kai], Pöpperl, M.[Maximillian], Gross, H.M.[Horst-Michael],
Points2Pix: 3D Point-Cloud to Image Translation Using Conditional GANs,
GCPR19(387-400).
Springer DOI 1911
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Knyaz, V.A.[Vladimir A.], Kniaz, V.V.[Vladimir V.], Remondino, F.[Fabio],
Image-to-Voxel Model Translation with Conditional Adversarial Networks,
4DPose18(I:601-618).
Springer DOI 1905
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Schaffert, R.[Roman], Wang, J.[Jian], Fischer, P.[Peter], Borsdorf, A.[Anja], Maier, A.[Andreas],
Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration,
GCPR18(140-152).
Springer DOI 1905
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Shen, Z., Ma, X., Zeng, X.,
Hybrid 3D Surface Description with Global Frames and Local Signatures of Histograms,
ICPR18(1610-1615)
IEEE DOI 1812
Histograms, Object recognition, Robustness, Feature extraction, Clutter, Interpolation, surface matching BibRef

Amayo, P.[Paul], Pinies, P.[Pedro], Paz, L.M.[Lina M.], Newman, P.[Paul],
Geometric Multi-model Fitting with a Convex Relaxation Algorithm,
CVPR18(8138-8146)
IEEE DOI 1812
Mathematical model, Data models, Optimization, Minimization, Measurement, Computational modeling, Estimation BibRef

Roth, S.[Stefan], Richter, S.R.[Stephan R.],
Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers,
CVPR18(1936-1944)
IEEE DOI 1812
2D encoding of 3D geometry. Shape, Decoding, Image reconstruction, Electron tubes, Image resolution BibRef

Seo, P.H.[Paul Hongsuck], Lee, J.M.[Jong-Min], Jung, D.[Deunsol], Han, B.H.[Bo-Hyung], Cho, M.[Minsu],
Attentive Semantic Alignment with Offset-Aware Correlation Kernels,
ECCV18(II: 367-383).
Springer DOI 1810
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Fathy, M.E.[Mohammed E.], Tran, Q.H.[Quoc-Huy], Zia, M.Z.[M. Zeeshan], Vernaza, P.[Paul], Chandraker, M.[Manmohan],
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences,
ECCV18(XV: 832-850).
Springer DOI 1810
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Jiang, C., Christie, D., Paudel, D.P., Demonceaux, C.,
High quality reconstruction of dynamic objects using 2D-3D camera fusion,
ICIP17(2209-2213)
IEEE DOI 1803
Cameras, Image reconstruction, Robustness, Surface reconstruction, Trajectory, Vehicle dynamics, RANSAC BibRef

Liu, L., Li, H., Dai, Y.,
Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map,
ICCV17(2391-2400)
IEEE DOI 1802
feature extraction, image matching, image sensors, query processing, 2D-3D direct feature matching framework, Visualization BibRef

Horanyi, N., Kato, Z.,
Multiview Absolute Pose Using 3D-2D Perspective Line Correspondences and Vertical Direction,
Multiview17(2472-2480)
IEEE DOI 1802
Cameras, Mathematical model, Pose estimation, Robustness, BibRef

Camposeco, F.[Federico], Sattler, T.[Torsten], Cohen, A.[Andrea], Geiger, A.[Andreas], Pollefeys, M.[Marc],
Toroidal Constraints for Two-Point Localization Under High Outlier Ratios,
CVPR17(6700-6708)
IEEE DOI 1711
Cameras, Computational modeling, Pose estimation, Solid modeling BibRef

Kong, C.[Chen], Zhu, R.[Rui], Kiani, H.[Hamed], Lucey, S.[Simon],
Structure from Category: A Generic and Prior-Less Approach,
3DV16(296-304)
IEEE DOI 1701
3D structure of generic objects, without motion. computer vision BibRef

Hess, A.[Andy], Ray, N.[Nilanjan], Zhang, H.[Hong],
Synthetic Viewpoint Prediction,
CRV16(391-398)
IEEE DOI 1612
neural networks; object viewpoint; pattern recognition Pose in 2D. BibRef

Mu, Z.,
A Fast DRR Generation Scheme for 3D-2D Image Registration Based on the Block Projection Method,
WBIR16(609-617)
IEEE DOI 1612
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Lähner, Z.[Zorah], Rodolŕ, E.[Emanuele], Schmidt, F.R.[Frank R.], Bronstein, M.M.[Michael M.], Cremers, D.[Daniel],
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching,
CVPR16(2185-2193)
IEEE DOI 1612
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Bansal, A., Russell, B.C.[Bryan C.], Gupta, A.,
Marr Revisited: 2D-3D Alignment via Surface Normal Prediction,
CVPR16(5965-5974)
IEEE DOI 1612
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Groueix, T.[Thibault], Fisher, M.[Matthew], Kim, V.G.[Vladimir G.], Russell, B.C.[Bryan C.], Aubry, M.[Mathieu],
3D-CODED: 3D Correspondences by Deep Deformation,
ECCV18(II: 235-251).
Springer DOI 1810
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Massa, F., Russell, B.C., Aubry, M.,
Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views,
CVPR16(6024-6033)
IEEE DOI 1612
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Aubry, M.[Mathieu], Maturana, D.[Daniel], Efros, A.A.[Alexei A.], Russell, B.C.[Bryan C.], Sivic, J.[Josef],
Seeing 3D Chairs: Exemplar Part-Based 2D-3D Alignment Using a Large Dataset of CAD Models,
CVPR14(3762-3769)
IEEE DOI 1409
3D BibRef

Wu, J.J.[Jia-Jun], Xue, T.F.[Tian-Fan], Lim, J.J.[Joseph J.], Tian, Y.D.[Yuan-Dong], Tenenbaum, J.B.[Joshua B.], Torralba, A.B.[Antonio B.], Freeman, W.T.[William T.],
Single Image 3D Interpreter Network,
ECCV16(VI: 365-382).
Springer DOI 1611
NN. 2D keypoints in 3D structure. BibRef

Tilly, N., Kelterbaum, D., Zeese, R.,
Geomorphological Mapping With Terrestrial Laser Scanning And UAV-based Imaging,
ISPRS16(B5: 591-597).
DOI Link 1610
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Bao, R., Iwamoto, K.,
Fast 2D-to-3D matching with camera pose voting for 3D object identification,
ICIP16(664-668)
IEEE DOI 1610
Cameras BibRef

Boerner, R., Kröhnert, M.,
Brute Force Matching Between Camera Shots And Synthetic Images From Point Clouds,
ISPRS16(B5: 771-777).
DOI Link 1610
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Liang, Y.B.[Yu-Bin], Qiu, Y.[Yan], Cui, T.J.[Tie-Jun],
Perspective Intensity Images For Co-registration Of Terrestrial Laser Scanner And Digital Camera,
ISPRS16(B3: 295-300).
DOI Link 1610
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Yang, Z.H., Zhang, Y.S., Zheng, T., Lai, W.B., Zou, Z.R., Zou, B.,
Co-registration Airborne Lidar Point Cloud Data And Synchronous Digital Image Registration Based On Combined Adjustment,
ISPRS16(B1: 259-264).
DOI Link 1610
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Rhodin, H.[Helge], Robertini, N.[Nadia], Richardt, C.[Christian], Seidel, H.P.[Hans-Peter], Theobalt, C.[Christian],
A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimation,
ICCV15(765-773)
IEEE DOI 1602
optimizing the overlap of the projected 3D shape model with images. BibRef

Brown, M., Windridge, D., Guillemaut, J.Y.,
Globally Optimal 2D-3D Registration from Points or Lines without Correspondences,
ICCV15(2111-2119)
IEEE DOI 1602
Annealing BibRef

Gao, Y., Huang, X., Zhang, F., Fu, Z., Yang, C.,
Automatic Geo-Referencing Mobile Laser Scanning Data to UAV Images,
UAV-g15(41-46).
DOI Link 1512
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Schmid, J.[Jérôme], Chęnes, C.[Christophe],
Segmentation of X-ray Images by 3D-2D Registration Based on Multibody Physics,
ACCV14(II: 674-687).
Springer DOI 1504
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Berkiten, S.[Sema], Fan, X.[Xinyi], Rusinkiewicz, S.[Szymon],
Merge2-3D: Combining Multiple Normal Maps with 3D Surfaces,
3DV14(440-447)
IEEE DOI 1503
Geometry BibRef

Hu, P.[Pan], Cai, H.M.[Hong-Ming], Bu, F.L.[Feng-Lin],
SLOREV: Using Classical CAD Techniques for 3D Object Extraction from Single Photo,
MMMod15(II: 491-501).
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Sweep-Loft-Revolve. BibRef

Liebold, F., Maas, H.G.,
Integrated Georeferencing of LiDAR and Camera Data Acquired from a Moving Platform,
PCV14(191-196).
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Kim, H.[Hyojin], Correa, C.D., Max, N.,
Automatic registration of LiDAR and optical imagery using depth map stereo,
ICCP14(1-8)
IEEE DOI 1411
cameras BibRef

Budzan, S.[Sebastian],
Fusion of Visual and Range Images for Object Extraction,
ICCVG14(108-115).
Springer DOI 1410
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Donoser, M.[Michael], Schmalstieg, D.[Dieter],
Discriminative Feature-to-Point Matching in Image-Based Localization,
CVPR14(516-523)
IEEE DOI 1409
Camera Pose Estimation; Classification; Image-based Localization BibRef

Xu, J.J.[Jie-Jun], Kim, K.[Kyungnam], Zhang, Z.Q.[Zhi-Qi], Chen, H.W.[Hai-Wen], Owechko, Y.[Yuri],
2D/3D Sensor Exploitation and Fusion for Enhanced Object Detection,
FusionOutdoor14(778-784)
IEEE DOI 1409
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Kroeger, T.[Till], Van Gool, L.J.[Luc J.],
Video Registration to SfM Models,
ECCV14(V: 1-16).
Springer DOI 1408
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Botterill, T.[Tom], Green, R.[Richard], Mills, S.[Steven],
A Decision-Theoretic Formulation for Sparse Stereo Correspondence Problems,
3DV14(224-231)
IEEE DOI 1503
Cameras BibRef

Khan, N., McCane, B., Mills, S.,
3D versus 2D based indoor image matching analysis on images from low cost mobile devices,
IVCNZ13(253-258)
IEEE DOI 1402
image matching BibRef

Yoruk, E., Vidal, R.,
Efficient Object Localization and Pose Estimation with 3D Wireframe Models,
3DRR13(538-545)
IEEE DOI 1403
feature extraction BibRef

Hao, Q.A.[Qi-Ang], Cai, R.[Rui], Li, Z.W.[Zhi-Wei], Zhang, L.[Lei], Pang, Y.W.[Yan-Wei], Wu, F.[Feng], Rui, Y.[Yong],
Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition,
CVPR13(899-906)
IEEE DOI 1309
BibRef

Park, H.S.[Hyun Soo], Wang, Y.[Yu], Nurvitadhi, E.[Eriko], Hoe, J.C.[James C.], Sheikh, Y.[Yaser], Chen, M.[Mei],
3D Point Cloud Reduction Using Mixed-Integer Quadratic Programming,
Geo-Loc13(229-236)
IEEE DOI 1309
Image localization. 2D image features and 3D point cloud. Based on training set of images to reduce the relevan 3D points. BibRef

Wang, J.[Jian], Riess, C.[Christian], Borsdorf, A.[Anja],
Sparse Depth Sampling for Interventional 2-D/3-D Overlay: Theoretical Error Analysis and Enhanced Motion Estimation,
CAIP13(86-93).
Springer DOI 1308
BibRef

Bahr, T., Jin, X., Lasica, R., Giessel, D.,
Image Registration of High-Resolution UAV Data: The New HYPARE Algorithm,
UAV-g13(17-19).
DOI Link 1311
BibRef

Bahr, T., Jin, X.,
Registration of Optical Data with High-Resolution SAR Data: A New Image Registration Solution,
Hannover13(19-21).
DOI Link 1308
BibRef

Givens, R.N.[Ryan N.], Walli, K.C.[Karl C.], Eismann, M.T.[Michael T.],
Evaluating the Lidar/HSI direct method for physics-based scene modeling,
AIPR14(1-6)
IEEE DOI 1504
BibRef
Earlier:
A multimodal approach to high resolution image classification,
AIPR13(1-7)
IEEE DOI 1408
BibRef
Earlier:
Fusion of LIDAR data with hyperspectral and high-resolution imagery for automation of DIRSIG scene generation,
AIPR12(1-7)
IEEE DOI 1307
BibRef
And: Alternate? AIPR12(1-7)
IEEE DOI 1307
Registration; fusion; synthetic imagery geophysical image processing. DIRSIG: Digital Imaging and Remote Sensing Image Generation Model BibRef

Matei, B.C., Valk, N.V.[N. Vander], Zhu, Z.W.[Zhi-Wei], Cheng, H.[Hui], Sawhney, H.S.,
Image to LIDAR matching for geotagging in urban environments,
WACV13(413-420).
IEEE DOI 1303
BibRef

Haque, M.N., Pickering, M.R., Biswas, M., Frater, M.R., Scarvell, J.M., Smith, P.N.,
A Slice Based Technique for Low-Complexity 3D/2D Registration of CT to Single Plane X-Ray Fluoroscopy,
DICTA12(1-6).
IEEE DOI 1303
BibRef

Wang, T.[Tao], He, X.M.[Xu-Ming], Barnes, N.M.[Nick M.],
Glass object segmentation by label transfer on joint depth and appearance manifolds,
ICIP13(2944-2948)
IEEE DOI 1402
BibRef
Earlier:
Glass object localization by joint inference of boundary and depth,
ICPR12(3783-3786).
WWW Link. 1302
with RGB-D camera. BibRef

Bodensteiner, C., Arens, M.,
Real-time 2D video/3D LiDAR registration,
ICPR12(2206-2209).
WWW Link. 1302
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Adan, A.[Antonio], Merchan, P.[Pilar], Salamanca, S.[Santiago],
Creating realistic 3D models from scanners by decoupling geometry and texture,
ICPR12(457-460).
WWW Link. 1302
Geometry and color/texture at different times. BibRef

Yang, H.[Heng], Liu, X.L.[Xiao-Lin], Patras, I.[Ioannis],
A simple and effective extrinsic calibration method of a camera and a single line scanning lidar,
ICPR12(1439-1442).
WWW Link. 1302
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Taneja, A.[Aparna], Ballan, L.[Luca], Pollefeys, M.[Marc],
City-Scale Change Detection in Cadastral 3D Models Using Images,
CVPR13(113-120)
IEEE DOI 1309
BibRef
Earlier:
Registration of Spherical Panoramic Images with Cadastral 3D Models,
3DIMPVT12(479-486).
IEEE DOI 1212
3D modeling; Change Detection; Large scale computer vision application BibRef

Carr, P.[Peter], Sheikh, Y.[Yaser], Matthews, I.D.[Iain D.],
Monocular Object Detection Using 3D Geometric Primitives,
ECCV12(I: 864-878).
Springer DOI 1210
BibRef

Fortenbury, B.R.[Billy Ray], Guerra-filho, G.[Gutemberg],
Robust 2d/3d Calibration Using RANSAC Registration,
ISVC12(I: 179-188).
Springer DOI 1209
BibRef

Rönnholm, P., Haggrén, H.,
Registration of Laser Scanning Point Clouds and Aerial Images Using Either Artificial Or Natural Tie Features,
AnnalsPRS(I-3), No. 2012, pp. 63-68.
DOI Link 1209
BibRef

Briese, C., Zach, G., Verhoeven, G., Ressl, C., Ullrich, A., Studnicka, N., Doneus, M.,
Analysis of Mobile Laser Scanning Data and Multi-View Image Reconstruction,
ISPRS12(XXXIX-B5:163-168).
DOI Link 1209
BibRef

Lagüela, S., Armesto, J., Arias, P., Zakhor, A.,
Automatic Procedure for The Registration of Thermographic Images With Point Clouds,
ISPRS12(XXXIX-B5:211-216).
DOI Link 1209
BibRef

Yao, C.J.[Chun-Jing], Gao, G.[Guang],
The Direct Registration of Lidar Point Clouds and High Resolution Image Based On Linear Feature By Introducing An Unknown Parameter,
ISPRS12(XXXIX-B4:403-408).
DOI Link 1209
BibRef

Homainejad, A.S.,
An Innovation Approach for Developing a 3D Model by Registering A Mono Image on a DTM,
ISPRS12(XXXIX-B4:189-194).
DOI Link 1209
BibRef

Chen, L.C., Lo, C.Y.,
Edge-based Registration for Airborne Imagery and Lidar Data,
ISPRS12(XXXIX-B3:265-268).
DOI Link 1209
BibRef

Chibunichev, A.G., Galakhov, V.P.,
Image To Point Cloud Method of 3d-modeling,
ISPRS12(XXXIX-B3:13-16).
DOI Link 1209
BibRef

Thivierge-Gaulin, D.[David], Chou, C.R.[Chen-Rui], Kiraly, A.P.[Atilla P.], Chef d'Hotel, C.[Christophe], Strobel, N.[Norbert], Cheriet, F.[Farida],
3D-2D Registration Based on Mesh-Derived Image Bisection,
WBIR12(70-78).
Springer DOI 1208
BibRef

Petre, R.D., Zaharia, T.,
3D Model-Based Sematic Labeling of 2D Objects,
DICTA11(152-157).
IEEE DOI 1205
Still image object categorization. 2D/3D matching techniques. BibRef

Jayawardena, S., Hutter, M., Brewer, N.,
A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation,
DICTA11(37-44).
IEEE DOI 1205
BibRef
Earlier:
Featureless 2D-3D pose estimation by minimising an illumination-invariant loss,
IVCNZ10(1-8).
IEEE DOI 1203
BibRef

Song, H.O.[Hyun Oh], Fritz, M.[Mario], Gu, C.H.[Chun-Hui], Darrell, T.J.[Trevor J.],
Visual grasp affordances from appearance-based cues,
RobPerc11(998-1005).
IEEE DOI 1201
From 2-D. BibRef

Wang, C.H.[Chao-Hui], Zeng, Y.[Yun], Simon, L.[Loic], Kakadiaris, I.[Ioannis], Samaras, D.[Dimitris], Paragios, N.[Nikos],
Viewpoint invariant 3D landmark model inference from monocular 2D images using higher-order priors,
ICCV11(319-326).
IEEE DOI 1201
BibRef

Sattler, T.[Torsten], Leibe, B.[Bastian], Kobbelt, L.[Leif],
Fast image-based localization using direct 2D-to-3D matching,
ICCV11(667-674).
IEEE DOI 1201
BibRef

Cheng, C.M.[Chia-Ming], Chen, H.W.[Hsiao-Wei], Lee, T.Y.[Tung-Ying], Lai, S.H.[Shang-Hong], Tsai, Y.H.[Ya-Hui],
Robust 3D object pose estimation from a single 2D image,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Swart, A.[Arjen], Broere, J.[Jonathan], Veltkamp, R.[Remco], Tan, R.[Robby],
Refined Non-rigid Registration of a Panoramic Image Sequence to a LiDAR Point Cloud,
PIA11(73-84).
Springer DOI 1110
BibRef

Sawada, Y.[Yoshihide], Hontani, H.[Hidekata],
A Comparison Study of Inferences on Graphical Model for Registering Surface Model to 3D Image,
MLMI11(257-264).
Springer DOI 1109
BibRef

Hanai, R., Yamazaki, K., Yaguchi, H., Okada, K., Inaba, M.,
Electric Appliance Parts Classification Using a Measure Combining the Whole Shape and Local Shape Distribution Similarities,
3DIMPVT11(296-303).
IEEE DOI 1109
BibRef

Baboud, L.[Lionel], Cadik, M.[Martin], Eisemann, E.[Elmar], Seidel, H.P.[Hans-Peter],
Automatic photo-to-terrain alignment for the annotation of mountain pictures,
CVPR11(41-48).
IEEE DOI 1106
BibRef

Pritt, M.D.[Mark D.], Gribbons, M.[Michael], La Tourette, K.[Kevin],
Automated cross-sensor registration, orthorectification and geopositioning using LIDAR digital elevation models,
AIPR10(1-6).
IEEE DOI 1010
BibRef

Imre, E.[Evren], Hilton, A.[Adrian],
Through-the-Lens Synchronisation for Heterogeneous Camera Networks,
BMVC12(97).
DOI Link 1301
BibRef

Imre, E.[Evren], Guillemaut, J.Y.[Jean-Yves], Hilton, A.[Adrian],
Calibration of Nodal and Free-Moving Cameras in Dynamic Scenes for Post-Production,
3DIMPVT11(260-267).
IEEE DOI 1109
BibRef
Earlier:
Moving Camera Registration for Multiple Camera Setups in Dynamic Scenes,
BMVC10(xx-yy).
HTML Version. 1009
Register the moving camera given a set of registered static views and 3-D model. BibRef

Meierhold, N., Spehr, M.[Marcel], Schilling, A., Gumhold, S.[Stefan], Maas, H.G.,
Automatic Feature Matching Between Digital Images And 2d Representations Of A 3d Laser Scanner Point Cloud,
CloseRange10(xx-yy).
PDF File. 1006

See also GPU-based Volumetric Reconstruction Of Trees From Multiple Images. BibRef

Zheng, H.W.[Hong-Wei], Cleju, I.[Ioan], Saupe, D.[Dietmar],
Highly-Automatic MI Based Multiple 2D/3D Image Registration Using Self-initialized Geodesic Feature Correspondences,
ACCV09(III: 426-435).
Springer DOI 0909
BibRef

Agrawal, A.[Anuraag], Matsumura, M.[Miki], Nakazawa, A.[Atsushi], Takemura, H.[Haruo],
Large-scale 3D scene modeling by registration of laser range data with Google Maps images,
ICIP09(589-592).
IEEE DOI 0911
BibRef

del Bue, A.[Alessio], Stosic, M.[Marko], Dodig, M.[Marija], Xavier, J.[Joao],
2D-3D registration of deformable shapes with manifold projection,
ICIP09(1061-1064).
IEEE DOI 0911
BibRef

Borgeat, L.[Louis], Poirier, G.[Guillaume], Beraldin, A.[Angelo], Godin, G.[Guy], Massicotte, P.[Philippe], Picard, M.[Michel],
A framework for the registration of color images with 3D models,
ICIP09(69-72).
IEEE DOI 0911
BibRef

Mei, L.[Liang], Liu, J.G.[Jin-Gen], Hero, A.O.[Alfred O.], Savarese, S.[Silvio],
Robust object pose estimation via statistical manifold modeling,
ICCV11(967-974).
IEEE DOI 1201
BibRef

Mei, L.[Liang], Sun, M.[Min], Carder, K.M.[Kevin M.], Hero, III, A.O.[Alfred O.], Savarese, S.[Silvio],
Unsupervised Object Pose Classification from Short Video Sequences,
BMVC09(xx-yy).
PDF File. 0909
Object pose from small camera movements. Cars, computer mouse. BibRef

Vasile, A., Waugh, F.R., Greisokh, D., Heinrichs, R.M.,
Automatic Alignment of Color Imagery onto 3D Laser Radar Data,
AIPR06(6-6).
IEEE DOI 0610
BibRef

Walli, K.C., Rhody, H.,
Automated image registration to 3-D scene models,
AIPR08(1-8).
IEEE DOI 0810
BibRef
Earlier: A1, Only:
Automated multisensor image registration,
AIPR03(103-107).
IEEE DOI 0310
BibRef

Trinder, J.C.[John C.], Salah, M.[Mahmoud],
Aerial Images and Lidar Data Fusion for Disaster Change Detection,
AnnalsPRS(I-4), No. 2012, pp. 227-232.
DOI Link 1209
BibRef

Salah, M.[Mahmoud], Trinder, J.C.[John C.], Shaker, A.[Ahmed], Hamed, M.[Mahmoud], Elsagheer, A.[Ali],
Aerial Images and Lidar Data Fusion for Automatic Feature Extraction using the Self-Organizing Map (SOM) Classifier,
Laser09(317). 0909
BibRef

Overett, G.[Gary], Petersson, L.[Lars],
Fast features for time constrained object detection,
FeatureSpace09(23-30).
IEEE DOI 0906
Learn feature points by matching to model. BibRef

Zhu, J.J.[Jie-Jie], Liao, M.[Miao], Yang, R.G.[Rui-Gang], Pan, Z.G.[Zhi-Geng],
Joint depth and alpha matte optimization via fusion of stereo and time-of-flight sensor,
CVPR09(453-460).
IEEE DOI 0906
Depth map and object boundaries. BibRef

Lin, Z.[Zhe], Hua, G.[Gang], Davis, L.S.[Larry S.],
Multi-scale shared features for cascade object detection,
ICIP12(1865-1868).
IEEE DOI 1302
BibRef
Earlier:
Multiple instance fFeature for robust part-based object detection,
CVPR09(405-412).
IEEE DOI 0906
Deal with features that are not always detected. Initial guess at object, then find features. BibRef

Mastin, A.[Andrew], Kepner, J.[Jeremy], Fisher, J.[John],
Automatic registration of LIDAR and optical images of urban scenes,
CVPR09(2639-2646).
IEEE DOI 0906
BibRef

Kaminsky, R.S.[Ryan S.], Snavely, N.[Noah], Seitz, S.M.[Steven M.], Szeliski, R.S.[Richard S.],
Alignment of 3D point clouds to overhead images,
InterNet09(63-70).
IEEE DOI 0906

See also Modeling the World from Internet Photo Collections. BibRef

Cho, P.[Peter], Snavely, N.[Noah],
3D exploitation of 2D ground-level & aerial imagery,
AIPR11(1-8).
IEEE DOI 1204
BibRef

Wang, L.[Lu], Neumann, U.[Ulrich],
A robust approach for automatic registration of aerial images with untextured aerial LiDAR data,
CVPR09(2623-2630).
IEEE DOI 0906
BibRef

Wang, Q.[Quan], Guan, W.[Wei], You, S.[Suya],
Augmented distinctive features for efficient image matching,
WACV11(15-22).
IEEE DOI 1101
BibRef

Wang, Q.[Quan], You, S.[Suya],
Explore multiple clues for urban images matching,
ICIP10(4621-4624).
IEEE DOI 1009
BibRef
Earlier:
Feature selection for real-time image matching systems,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Wang, L.[Lu], Neumann, U.[Ulrich], You, S.[Suya],
Wide-baseline image matching using Line Signatures,
ICCV09(1311-1318).
IEEE DOI 0909
BibRef

Wang, L.[Lu], You, S.[Suya], Neumann, U.[Ulrich],
Semiautomatic registration between ground-level panoramas and an orthorectified aerial image for building modeling,
VRML07(1-8).
IEEE DOI 0710

See also Generating and Updating Textures for a Large-Scale Environment. BibRef

von Hansen, W.[Wolfgang], Gross, H.[Hermann], Thoennessen, U.[Ulrich],
Line-Based Registration of Terrestrial and Airborne LIDAR Data,
ISPRS08(B3a: 161 ff).
PDF File. 0807
BibRef

Lewis, P.[Paul], McElhinney, C.[Conor], Schön, B.[Bianca], McCarthy, T.[Tim],
Mobile Mapping System LIDAR Data Framework,
GeoInfo10(xx-yy).
PDF File. 1011
BibRef

McCarthy, T.[Timothy], Zheng, J.H.[Jiang-Hua], Fotheringham, A.S.[A. Stewart],
Integration of dynamic LiDAR and image sensor data for route corridor mapping,
ISPRS08(B5: 1125 ff).
PDF File. 0807
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Bienert, A.[Anne], Maas, H.G.[Hans-Gerd],
Methods for the automatic geometric registration of terrestrial laser scanner point clouds in forest stands,
Laser09(93). 0909

See also Tree Detection and Diameter Estimations by Analysis of Forest Terrestrial Laserscanner Point Clouds. BibRef

Huang, J.[Jing], You, S.[Suya],
Point cloud labeling using 3D Convolutional Neural Network,
ICPR16(2670-2675)
IEEE DOI 1705
BibRef
Earlier:
Point cloud matching based on 3D self-similarity,
PCP12(41-48).
IEEE DOI 1207
Labeling, Neural networks, Testing, Training, Training data, BibRef

Huang, J.[Jing], You, S.[Suya], Zhao, J.P.[Jia-Ping],
Multimodal image matching using self similarity,
AIPR11(1-6).
IEEE DOI 1204
BibRef

Wang, Q.[Quan], You, S.[Suya],
A vision-based 2D-3D registration system,
WACV09(1-8).
IEEE DOI 0912
BibRef
Earlier:
Real-Time Image Matching Based on Multiple View Kernel Projection,
Fusion07(1-8).
IEEE DOI 0706
BibRef

Meierhold, N.[Nadine], Schmich, A.[Armin],
Referencing of images to laser scanner data using linear features extracted from digital images and range images,
Laser09(164). 0909
BibRef

Meierhold, N.[Nadine], Bienert, A., Schmich, A.[Armin],
Line-Based Referencing between Images and Laser Scanner Data for Image-Based Point Cloud Interpretation in a CAD-Environment,
ISPRS08(B5: 437 ff).
PDF File. 0807
BibRef

Kang, Z.Z.[Zhi-Zhong],
Automatic Registration of Terrestrial Point Cloud Using Panoramic Reflectance Images,
ISPRS08(B5: 431 ff).
PDF File. 0807
BibRef

Sotoodeh, S., Gruen, A., Hanusch, T.,
Integration of Structured Light and Digital Camera Image Data for the 3D Reconstruction of an Ancient Globe,
ISPRS08(B5: 367 ff).
PDF File. 0807
BibRef

Novák, D.[David],
Semi-Automatic Orientation of Images With Respect to a Point Cloud System,
ISPRS08(B3b: 295 ff).
PDF File. 0807
BibRef

Rönnholm, P.[Petri], Honkavaara, E.[Eija], Erving, A.[Anna], Nuikka, M.[Milka], Haggrén, H.[Henrik], Kaasalainen, S.[Sanna], Hyyppä, H.[Hannu], Hyyppä, J.[Juha],
Registration of Airborne Laser Scanning Point Clouds with Aerial Images through Terrestrial Image Blocks,
ISPRS08(B1: 473 ff).
PDF File. 0807
BibRef

Deng, F.[Fei], Hu, M.J.[Min-Jie], Guan, H.Y.[Hai-Yan],
Automatic Registration Between LIDAR and Digital Images,
ISPRS08(B1: 487 ff).
PDF File. 0807
BibRef

Ding, M.[Min], Lyngbaek, K.[Kristian], Zakhor, A.[Avideh],
Automatic registration of aerial imagery with untextured 3D LiDAR models,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Beder, C.[Christian], Schiller, I.[Ingo], Koch, R.[Reinhard],
Photoconsistent Relative Pose Estimation between a PMD 2D3D-Camera and Multiple Intensity Cameras,
DAGM08(xx-yy).
Springer DOI 0806
BibRef

Yan, P.K.[Ping-Kun], Khan, S.M.[Saad M.], Shah, M.[Mubarak],
3D Model based Object Class Detection in An Arbitrary View,
ICCV07(1-6).
IEEE DOI 0710
Match 2D image to 3D model. BibRef

Grest, D.[Daniel], Petersen, T.[Thomas], Krüger, V.[Volker],
A Comparison of Iterative 2D-3D Pose Estimation Methods for Real-Time Applications,
SCIA09(706-715).
Springer DOI 0906
BibRef

Franz, M.O.[Matthias O.], Stamminger, M.[Marc],
2D-3D-Registration in Computer Tomography without an initial pose,
VMV06(229-236).
WWW Link. BibRef 0600

Ryberg, A., Christiansson, A.K., Eriksson, K.,
Accuracy Investigation of a Vision Based System for Pose Measurements,
ICARCV06(1-6).
IEEE DOI 0612
BibRef

Decker, P.[Peter], Paulus, D.[Dietrich], Feldmann, T.[Tobias],
Dealing with degeneracy in essential matrix estimation,
ICIP08(1964-1967).
IEEE DOI 0810
BibRef

Kubias, A.[Alexander], Deinzer, F.[Frank], Feldmann, T.[Tobias], Paulus, D.[Dietrich],
Extended Global Optimization Strategy for Rigid 2D/3D Image Registration,
CAIP07(759-767).
Springer DOI 0708
BibRef

Barrois, B.[Bjorn], Wohler, C.[Christian],
3D Pose Estimation Based on Multiple Monocular Cues,
BenCOS07(1-8).
IEEE DOI 0706
Compare image to synthetic image from CAD model. BibRef

Di, H.J.[Hui-Jun], Iqbal, R.N.[Rao Naveed], Xu, G.Y.[Guang-You], Tao, L.M.[Lin-Mi],
Groupwise Shape Registration on Raw Edge Sequence via A Spatio-Temporal Generative Model,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Liebelt, J.[Joerg], Schmid, C.[Cordelia],
Multi-view object class detection with a 3D geometric model,
CVPR10(1688-1695).
IEEE DOI 1006
BibRef

Liebelt, J.[Joerg], Schmid, C.[Cordelia], Schertler, K.[Klaus],
Viewpoint-independent object class detection using 3D Feature Maps,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Liebelt, J.[Joerg], Schertler, K.[Klaus],
Precise Registration of 3D Models To Images by Swarming Particles,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Hong, H.[Helen], Kim, K.[Kyehyun], Park, S.J.[Seong-Jin],
Fast 2D-3D Point-Based Registration Using GPU-Based Preprocessing for Image-Guided Surgery,
CIARP06(218-226).
Springer DOI 0611
BibRef

Al-Manasir, K., Fraser, C.S.,
Automatic registration of terrestrial laserscanner data via imagery,
IEVM06(xx-yy).
PDF File. 0609
BibRef

Pong, H.K.[Hon-Keat], Cham, T.J.[Tat-Jen],
Optimal Cascade Construction for Detection using 3D Models,
ICPR06(I: 808-811).
IEEE DOI 0609
BibRef
Earlier:
Object Detection Using a Cascade of 3D Models,
ACCV06(II:284-293).
Springer DOI 0601
Alignment for detection. Hierarchy of models. BibRef

Pong, H.K.[Hon-Keat], Cham, T.J.[Tat-Jen],
Alignment of 3D Models to Images Using Region-Based Mutual Information and Neighborhood Extended Gaussian Images,
ACCV06(I:60-69).
Springer DOI 0601
BibRef

Lipikorn, R.[Rajalida], Shimizu, A.[Akinobu], Kobatake, H.[Hidefumi],
Three-Dimensional Object Recognition Using a Modified Exoskeleton and Extended Hausdorff Distance Matching Algorithm,
ICIAR04(I: 697-704).
Springer DOI 0409
BibRef

Janko, Z., Chetverikov, D.,
Photo-consistency based registration of an uncalibrated image pair to a 3D surface model using genetic algorithm,
3DPVT04(616-622).
IEEE DOI 0412
BibRef
And:
Registration of an uncalibrated image pair to a 3d surface model,
ICPR04(II: 208-211).
IEEE DOI 0409

See also Pre-registration of arbitrarily oriented 3D surfaces using a genetic algorithm. BibRef

Liu, Q., Lou, J., Hu, W., Tan, T.,
Pose Evaluation Based on Bayesian classification Error,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Morris, R.D.[Robin D.], Smelyanskiy, V.N.[Vadim N.], Cheeseman, P.C.[Peter C.],
Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction,
EMMCVPR01(105-117).
Springer DOI 0205
BibRef

Schultz, H., Woo, D., Stolle, F.R., Riseman, E.M.,
Error Detection and DEM Fusion using Self-Consistency,
ICCV99(1174-1181).
IEEE DOI BibRef 9900

Leventon, M.E., Wells, III, W.M., Grimson, W.E.L.,
Multiple View 2D-3D Mutual Information Registration,
DARPA97(625-630). BibRef 9700

Ferrell, C.,
Orientation Behavior Using Registered Topographic Maps,
DARPA97(1367-1372). BibRef 9700

Connolly, C.I., Mundy, J.L., Stenstrom, J.R., and Thompson, D.W.,
Matching from 3-D Range Models into 2-D Intensity Scenes,
ICCV87(65-72). The model is a range scene, the image is the intensity image.
See also Constructing Object Models from Multiple Images. BibRef 8700

Thompson, D.W., Mundy, J.L.,
Three Dimensional Model Matching from an Unconstrained Viewpoint,
CRA87(208-220). BibRef 8700

Quan, L.[Long], Mohr, R., Thirion, E.,
Generating the initial hypothesis using perspective invariants for a 2D image and 3D model matching,
ICPR88(II: 872-874).
IEEE DOI 8811
BibRef

Little, J.J.,
Automatic Registration of Landsat MSS Images to Digital Elevation Models,
CVWS82(178-184). BibRef 8200

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Range Data Matching -- Accumulation Methods .


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