12.3.4 Surfaces and Range Data Matching

Shirai, Y.[Yoshiaki],
Recognition of Polyhedrons with a Range Finder,
PR(4), No. 3, October 1972, pp. 243-244.
Elsevier DOI BibRef 7210
And: Bul. Electrotech. Lab.(35), No. 3, 1971, pp. 290-296. BibRef
Earlier: With: Suwa, M., IJCAI71(80-87). Compute the planes and match according to the relations between planes. BibRef

Oshima, M.[Masaki], Shirai, Y.[Yoshiaki],
A Scene Description Method Using Three Dimensional Information,
PR(11), No. 1, 1979, pp. 9-17.
Elsevier DOI BibRef 7900

Oshima, M.[Masaki], Shirai, Y.[Yoshiaki],
Object Recognition Using Three-Dimensional Information,
PAMI(5), No. 4, July 1983, pp. 353-361. BibRef 8307
Earlier: IJCAI81(601-606). Recognize Three-Dimensional Objects. Use a vertical slit projector and a TV to get the range. Surface orientation from a few points (assume they are planes). Elementary regions from similar orientations. Classify regions as planar or curved, extend and merge curved regions. Matching: Choose a kernel (2 regions, planar, many neighbors, large, adjacent). The kernel forces the match for the other regions. The kernel can be only 1 region if that is all that qualifies. BibRef

Bhanu, B.[Bir],
Representation and Shape Matching of 3-D Objects,
PAMI(6), No. 3, May 1984, pp. 340-351. BibRef 8405
Earlier:
Surface Representation and Shape Matching of 3-D Objects,
PRIP82(349-354). Analysis of the laser ranger data to generate surfaces (near planar regions). And matching of these representations to identify the object. BibRef

Bhanu, B.[Bir], and Nuttall, L.A.[Lawrence A.],
Recognition of 3-D Objects in Range Images Using a Butterfly Multiprocessor,
PR(22), No. 1, 1989, pp. 49-64.
Elsevier DOI BibRef 8900

Goldgof, D.B., Huang, T.S., and Lee, H.,
A Curvature-Based Approach to Terrain Recognition,
PAMI(11), No. 11, November 1989, pp. 1213-1217.
IEEE DOI BibRef 8911
Earlier: CVPR88(899-904).
IEEE DOI Surface segmentation by iterative growing regions. Match the three-dimensional terrain maps using curvature and fit a surface to the data. See the comparison:
See also Experimental Comparison of Range Image Segmentation Algorithms, An. BibRef

Mulgaonkar, P.G., Cowan, C.K., and de Curtins, J.,
Understanding Object Configurations Using Range Images,
PAMI(14), No. 2, February 1992, pp. 303-307.
IEEE DOI BibRef 9202

Maes, F., Collignon, A., Vandermeulen, D.[Dirk], Suetens, P.[Paul], Marchal, G.,
Multimodality Image Registration by Maximization of Mutual Information,
MedImg(16), No. 2, April 1997, pp. 187-198.
IEEE Top Reference. 0205
BibRef
Earlier: A1, A2, A3, A5, A4: MMBIA96(REGISTRATION I) BibRef

Collignon, A., Vandermeulen, D., Suetens, P., Marchal, G.,
Registration of 3D Multimodality Medical Images Using Surfaces and Point Landmarks,
PRL(15), No. 5, May 1994, pp. 461-467. BibRef 9405
Earlier:
3D Multi-Modality Medical Image Registration Using Feature Space Clustering,
CVRMed95(XX-YY) BibRef

Claes, P., Vandermeulen, D., Van Gool, L.J., Suetens, P.,
Robust and accurate partial surface registration based on variational implicit surfaces for automatic 3D model building,
3DIM05(385-392).
IEEE DOI 0508
BibRef

Claes, P., Vandermeulen, D., Van Gool, L.J., Suetens, P.[Paul],
Partial surface integration based on variational implicit functions and surfaces for 3D model building,
3DIM05(31-38).
IEEE DOI 0508
BibRef

Bergevin, R., Laurendeau, D.[Denis], Poussart, D.,
Registering Range Views of Multipart Objects,
CVIU(61), No. 1, January 1995, pp. 1-16.
DOI Link BibRef 9501
Earlier:
Estimating the 3D Rigid Transformation Between Two Range Views of a Complex Object,
ICPR92(I:478-482).
IEEE DOI BibRef

Godin, G., Laurendeau, D.[Denis], Bergevin, R.,
A method for the registration of attributed range images,
3DIM01(179-186).
IEEE DOI 0106
BibRef

Bergevin, R., Soucy, M., Gagnon, H., and Laurendeau, D.[Denis],
Towards a General Multiview Registration Technique,
PAMI(18), No. 5, May 1996, pp. 540-547.
IEEE DOI 9606
Combine multiple range images inot one.
See also General Surface Approach to the Integration of a Set of Range Views, A. BibRef

Gagnon, H., Soucy, M., Bergevin, R., Laurendeau, D.[Denis],
Registration of Multiple Range Views for Automatic 3-D Model Building,
CVPR94(581-586).
IEEE DOI BibRef 9400

Higuchi, K.[Kazunori], Hebert, M.[Martial], Ikeuchi, K.[Katsushi],
Building 3-D Models from Unregistered Range Images,
GMIP(57), No. 4, July 1995, pp. 315-333. BibRef 9507
And: MfR01(Chapter I-2). BibRef
And: CMU-CS-TR-93-214, November 1993.
PS File. BibRef

Fisher, R.B.[Robert B.],
From Surfaces to Objects: Computer Vision and Three Dimensional Scene Analysis,
Wiley1989. ISBN 0471923443. BibRef 8900 Edinburgh
WWW Link. BibRef

Fillatreau, P., and Fisher, R.B.,
Non-Polyhedral Landmark Recognition using 3D Depth Images and Partially Correct Models,
SIRS95(271-278). BibRef 9500
Earlier: DAI-No. 752, June 1995. BibRef Edinburgh BibRef

Fisher, R.B., Fitzgibbon, A.W., Waite, M., Orr, M., and Trucco, E.,
Recognition of Complex 3-D Objects from Range Data,
CIAP93(509-606). 3D object recognition
PS File. BibRef 9300 Edinburgh BibRef

Bispo, E.M., Fitzgibbon, A.W., Fisher, R.B.,
Visually Salient 3D Model Acquisition from Range Data,
BMVC93(619-628).
PDF File. automatic 3D shape model acquisition from range data
PS File. BibRef 9300 Edinburgh BibRef

Fisher, R.B.[Robert B.],
Using Surfaces and Object Models to Recognize Partially Obscured Objects,
IJCAI83(989-995). BibRef 8300 Edinburgh Recognize Three-Dimensional Objects. Hypothesize the location based on matching surfaces and a model. Describe the input data in terms of the model, verify the vmatch. BibRef

Thirion, J.P.,
New Feature Points Based on Geometric Invariants for 3D Image Registration,
IJCV(18), No. 2, May 1996, pp. 121-137.
Springer DOI 9608
BibRef
Earlier:
Extremal Points: Definition and Application to 3D Image Registration,
CVPR94(587-592).
IEEE DOI BibRef

Shashua, A.[Amnon], and Toelg, S.[Sebastian],
The Quadric Reference Surface: Theory and Applications,
IJCV(23), No. 2, June 1997, pp. 185-198.
DOI Link 9708
BibRef
Earlier: ARPA94(II:1451-1459). BibRef
And: MIT AI Memo-1448, June 1994.
WWW Link. BibRef
And:
The Quadric Reference Surface: Applications in Registering Views of Complex 3D Objects,
ECCV94(B:407-416).
Springer DOI BibRef

Ham, Y.K.[Young Kug], Park, R.H.[Rae-Hong],
3D Object Recognition in Range Images Using Hidden Markov Models and Neural Networks,
PR(32), No. 5, May 1999, pp. 729-742.
Elsevier DOI
See also Hybrid Approaches to Frontal View Face Recognition Using the Hidden Markov Model and Neural-Network. BibRef 9905

Gruen, A.[Armin], Akca, D.[Devrim],
Least squares 3D surface and curve matching,
PandRS(59), No. 3, May 2005, pp. 151-174.
Elsevier DOI 0509
BibRef
Earlier: A2, A1:
Fast correspondence search for 3D surface matching,
Laser05(xx-yy).
PDF File. 0509
BibRef

Liu, H.[Heng], Yan, J.Q.[Jing-Qi], Zhang, D.[David],
What is wrong with mesh PCA in coordinate direction normalization,
PR(39), No. 11, November 2006, pp. 2244-2247.
Elsevier DOI 0608
Mesh PCA; Surface registration; Coordinate direction normalization BibRef

Refice, A., Bovenga, F., Nutricato, R.,
MST-Based Stepwise Connection Strategies for Multipass Radar Data, With Application to Coregistration and Equalization,
GeoRS(44), No. 8, August 2006, pp. 2029-2040.
IEEE DOI 0608
BibRef

Sampat, M.P.[Mehul P.], Wang, Z.[Zhou], Gupta, S.[Shalini], Bovik, A.C.[Alan C.], Markey, M.K.[Mia K.],
Complex Wavelet Structural Similarity: A New Image Similarity Index,
IP(18), No. 11, November 2009, pp. 2385-2401.
IEEE DOI 0911
BibRef
Earlier: A3, A1, A5, A4, A2:
Facial Range Image Matching Using the Complex Wavelet Structural Similarity Metric,
WACV07(4-4).
IEEE DOI 0702
BibRef

Rehman, A.[Abdul], Gao, Y.[Yang], Wang, J.[Jiheng], Wang, Z.[Zhou],
Image classification based on complex wavelet structural similarity,
SP:IC(28), No. 8, 2013, pp. 984-992.
Elsevier DOI 1309
Complex-wavelet structural similarity BibRef

Hillenbrand, U.[Ulrich], Fuchs, A.[Alexander],
An experimental study of four variants of pose clustering from dense range data,
CVIU(115), No. 10, October 2011, pp. 1427-1448.
Elsevier DOI 1108
Robust estimation; Pose estimation; Range data; Parameter density; Clustering; Performance evaluation BibRef

Sipiran, I.[Ivan], Meruane, R.[Rafael], Bustos, B.[Benjamin], Schreck, T.[Tobias], Li, B.[Bo], Lu, Y.J.[Yi-Juan], Johan, H.[Henry],
A benchmark of simulated range images for partial shape retrieval,
VC(30), No. 11, November 2014, pp. 1293-1308.
Springer DOI 1411
partial views which are used as queries. BibRef

Al-Osaimi, F.R.,
A Novel Multi-Purpose Matching Representation of Local 3D Surfaces: A Rotationally Invariant, Efficient, and Highly Discriminative Approach With an Adjustable Sensitivity,
IP(25), No. 2, February 2016, pp. 658-672.
IEEE DOI 1601
Accuracy BibRef

Khalid, S.[Shehzad], Sajjad, S.[Sadaf], Jabbar, S.[Sohail], Chang, H.[Hangbae],
Accurate and efficient shape matching approach using vocabularies of multi-feature space representations,
RealTimeIP(13), No. 3, September 2017, pp. 449-465.
Springer DOI 1710
BibRef

Escudero-Viñolo, M.[Marcos], Bescos, J.[Jesus],
Severe-occluded 3D object identification via region-based descriptions,
SP:IC(58), No. 1, 2017, pp. 240-257.
Elsevier DOI 1710
3D-object identification BibRef

Furuya, T.[Takahiko], Ohbuchi, R.[Ryutarou],
Learning part-in-whole relation of 3D shapes for part-based 3D model retrieval,
CVIU(166), No. 1, 2018, pp. 102-114.
Elsevier DOI 1712
BibRef
Earlier: A2, A1:
Distance metric learning and feature combination for shape-based 3D model retrieval,
3DOR10(63-68).
DOI Link 1111
BibRef
Earlier: A1, A2:
Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features,
CIVR09(Article No 26).
DOI Link 0907
BibRef
Earlier: A2, A1:
Scale-weighted dense bag of visual features for 3D model retrieval from a partial view 3D model,
S3DV09(63-70).
IEEE DOI 0910
Part-based 3D model retrieval BibRef

Gao, Z., Wang, D.Y., Xue, Y.B., Xu, G.P., Zhang, H., Wang, Y.,
3D object recognition based on pairwise Multi-view Convolutional Neural Networks,
JVCIR(56), 2018, pp. 305-315.
Elsevier DOI 1811
3D object recognition, CNN, Multi-view, PMV-CNN, Pairwise, End-to-end BibRef

Yang, J., Quan, S., Wang, P., Zhang, Y.,
Evaluating Local Geometric Feature Representations for 3D Rigid Data Matching,
IP(29), 2020, pp. 2522-2535.
IEEE DOI 2001
Performance evaluation, 3D point cloud, local descriptors, feature representation, 3D matching BibRef

Ao, S.[Sheng], Guo, Y.L.[Yu-Lan], Tian, J.D.[Jin-Dong], Tian, Y.[Yong], Li, D.[Dong],
A repeatable and robust local reference frame for 3D surface matching,
PR(100), 2020, pp. 107186.
Elsevier DOI 2005
Local reference frame, 3D Surface description, Feature transformation, Local characteristics, Scale strategy BibRef

Xiao, G.B.[Guo-Bao], Ma, J.Y.[Jia-Yi], Wang, S.P.[Shi-Ping], Chen, C.W.[Chang-Wen],
Deterministic Model Fitting by Local-Neighbor Preservation and Global-Residual Optimization,
IP(29), 2020, pp. 8988-9001.
IEEE DOI 2009
Data models, Computational modeling, Analytical models, Optimization, Approximation algorithms, multiple-structure data BibRef

Hu, B.[Bo], Zhou, S.L.[Sheng-Long], Xiong, Z.W.[Zhi-Wei], Wu, F.[Feng],
Cross-Resolution Distillation for Efficient 3D Medical Image Registration,
CirSysVideo(32), No. 10, October 2022, pp. 7269-7283.
IEEE DOI 2210
Computational modeling, Strain, Image registration, Deformable models, Graphics processing units, deep learning BibRef

Sheik, N.A.[Noaman Akbar], Veelaert, P.[Peter], Deruyter, G.[Greet],
Registration of Building Scan with IFC-Based BIM Using the Corner Points,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Liu, F.[Feng], Liu, X.M.[Xiao-Ming],
Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects,
PAMI(46), No. 3, March 2024, pp. 1852-1867.
IEEE DOI 2402
Shape, Semantics, Uncertainty, Strain, Probabilistic logic, Data models, Dense 3D shape correspondence, generic objects, unsupervised learning BibRef

Zhao, B.[Bao], Wang, Z.[Zihan], Chen, X.B.[Xiao-Bo], Fang, X.Y.[Xian-Yong], Jia, Z.H.[Zhao-Hong],
FApSH: An effective and robust local feature descriptor for 3D registration and object recognition,
PR(151), 2024, pp. 110354.
Elsevier DOI 2404
3D feature description, Point cloud, 3D registration, Local reference axis BibRef

Liu, Y.[Yang], Tao, K.[Keda], Tian, T.[Tianhui], Gao, X.B.[Xin-Bo], Han, J.G.[Jun-Gong], Shao, L.[Ling],
Transductive zero-shot learning with generative model-driven structure alignment,
PR(153), 2024, pp. 110561.
Elsevier DOI 2405
Domain shift, Transductive zero-shot learning, Structure alignment BibRef

Chen, Y.[Yifu], Le, Y.[Yuan], Wu, L.[Lin], Zhang, D.F.[Dong-Fang], Zhao, Q.[Qian], Zhang, X.[Xueman], Liu, L.[Lu],
Weak-Texture Seafloor and Land Image Matching Using Homography-Based Motion Statistics with Epipolar Geometry,
RS(16), No. 14, 2024, pp. 2683.
DOI Link 2408
BibRef

Fan, M.[Miao], Chen, M.[Mingrui], Hu, C.[Chen], Zhou, S.C.[Shu-Chang],
Occ2Net: Robust Image Matching Based on 3D Occupancy Estimation for Occluded Regions,
ICCV23(9618-9628)
IEEE DOI 2401
model the occlusions in the match. BibRef

Hao, Y.[Yu], Fang, Y.[Yi],
3D Unsupervised Region-Aware Registration Transformer,
ICIP23(2780-2784)
IEEE DOI 2312
BibRef

Yang, Z.Y.[Zhi-Yuan], Zhang, Q.F.[Qing-Fu],
Towards Modeling 3D Dense Shape Correspondence from Category-Specific Multi-View Images,
ICIP23(445-449)
IEEE DOI 2312
BibRef

Gao, M.L.[Mao-Lin], Roetzer, P.[Paul], Eisenberger, M.[Marvin], Lähner, Z.[Zorah], Moeller, M.[Michael], Cremers, D.[Daniel], Bernard, F.[Florian],
SIGMA: Scale-Invariant Global Sparse Shape Matching,
ICCV23(645-654)
IEEE DOI 2401
BibRef

Cao, D.L.[Dong-Liang], Bernard, F.[Florian],
Unsupervised Deep Multi-Shape Matching,
ECCV22(III:55-71).
Springer DOI 2211
BibRef

Meltzer, P.[Peter], Shayani, H.[Hooman], Khasahmadi, A.[Amir], Jayaraman, P.K.[Pradeep Kumar], Sanghi, A.[Aditya], Lambourne, J.[Joseph],
UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps,
ICCV21(9670-9679)
IEEE DOI 2203
Point cloud compression, Industries, Solid modeling, Shape, Shape measurement, Representation learning, Vision applications and systems BibRef

Feng, W.Q.[Wan-Quan], Zhang, J.Y.[Ju-Yong], Cai, H.R.[Hong-Rui], Xu, H.F.[Hao-Fei], Hou, J.H.[Jun-Hui], Bao, H.J.[Hu-Jun],
Recurrent Multi-view Alignment Network for Unsupervised Surface Registration,
CVPR21(10292-10302)
IEEE DOI 2111
Training, Shape, Shape measurement, Training data, Loss measurement BibRef

Duan, Y.Q.[Yue-Qi], Zhu, H.D.[Hai-Dong], Wang, H.[He], Yi, L.[Li], Nevatia, R.[Ram], Guibas, L.J.[Leonidas J.],
Curriculum DeepSDF,
ECCV20(VIII:51-67).
Springer DOI 2011
Signed Distance Function. Learn more complex shapes. BibRef

Wang, Y.Q.[Yi-Qun], Guo, J.W.[Jian-Wei], Yan, D.M.[Dong-Ming], Wang, K.[Kai], Zhang, X.P.[Xiao-Peng],
A Robust Local Spectral Descriptor for Matching Non-Rigid Shapes With Incompatible Shape Structures,
CVPR19(6224-6233).
IEEE DOI 2002
BibRef

Lu, Z., Yang, G., Hua, T., Hu, L., Kong, Y., Tang, L., Zhu, X., Dillenseger, J., Shu, H., Coatrieux, J.,
Unsupervised Three-Dimensional Image Registration Using a Cycle Convolutional Neural Network,
ICIP19(2174-2178)
IEEE DOI 1910
Image registration, 3D, unsupervised, non-rigid, convolutional neural network BibRef

Kundu, A.[Abhijit], Li, Y.[Yin], Rehg, J.M.[James M.],
3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare,
CVPR18(3559-3568)
IEEE DOI 1812
Shape, Solid modeling, Task analysis, Computational modeling, Image reconstruction BibRef

Xia, F.[Fei], Zamir, A.R.[Amir R.], He, Z.Y.[Zhi-Yang], Sax, A.[Alexander], Malik, J.[Jitendra], Savarese, S.[Silvio],
Gibson Env: Real-World Perception for Embodied Agents,
CVPR18(9068-9079)
IEEE DOI 1812
Learn a simulation, apply to real world. Rendering (computer graphics), Cameras, Neural networks, Visualization, Physics, Robot sensing systems BibRef

Grabner, A.[Alexander], Roth, P.M.[Peter M.], Lepetit, V.[Vincent],
3D Pose Estimation and 3D Model Retrieval for Objects in the Wild,
CVPR18(3022-3031)
IEEE DOI 1812
Estimate pose, then retrieve 3D model to represent the object. Match rendered model images to data. Solid modeling, Computational modeling, Predictive models, Rendering (computer graphics) BibRef

Xing, X.X.[Xiao-Xia], Cai, Y.H.[Ying-Hao], Lu, T.[Tao], Cai, S.J.[Shao-Jun], Yang, Y.P.[Yi-Ping], Wen, D.Y.[Da-Yong],
3DTNet: Learning Local Features Using 2D and 3D Cues,
3DV18(435-443)
IEEE DOI 1812
feature extraction, image matching, image representation, image texture, local geometry feature BibRef

Radenovic, F.[Filip], Tolias, G.[Giorgos], Chum, O.[Ondrej],
Deep Shape Matching,
ECCV18(VI: 774-791).
Springer DOI 1810
BibRef

Litany, O., Remez, T., Rodolà, E.[Emanuele], Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.],
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence,
ICCV17(5660-5668)
IEEE DOI 1802
learning (artificial intelligence), solid modelling, deep functional maps, deep residual network, Training BibRef

Xie, J.[Jin], Wang, M.[Meng], Fang, Y.[Yi],
Learned Binary Spectral Shape Descriptor for 3D Shape Correspondence,
CVPR16(3309-3317)
IEEE DOI 1612
BibRef

Zhang, Z.L.[Zong-Liang], Li, J.[Jonathan], Li, X.[Xin], Lin, Y.B.[Yang-Bin], Zhang, S.X.[Shan-Xin], Wang, C.[Cheng],
A Fast Method For Measuring The Similarity Between 3d Model And 3d Point Cloud,
ISPRS16(B1: 725-728).
DOI Link 1610
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Karmakar, N.[Nilanjana], Biswas, A.[Arindam],
Shape Matching of 3D Topologically Segmented Objects,
CTIC16(170-179).
Springer DOI 1608
BibRef

Bianchi, M.[Mariano], Heredia, N.[Nadia], Gómez-Fernández, F.[Francisco], Pardo, A.[Alvaro], Mejail, M.[Marta],
Two Applications of RGB-D Descriptors in Computer Vision,
CIARP15(236-244).
Springer DOI 1511
Spin-images, CSHOT and ECV. Object recognition and object tracking. BibRef

Roure, F.[Ferran], Diez, Y.[Yago], Llado, X.[Xavier], Forest, J.[Josep], Pribanic, T.[Tomislav], Salvi, J.[Joaquim],
A study on the robustness of shape descriptors to common scanning artifacts,
MVA15(522-525)
IEEE DOI 1507
Data models. For registration. BibRef

Yoshiyasu, Y.[Yusuke], Yoshida, E.[Eiichi], Yokoi, K.[Kazuhito], Sagawa, R.[Ryusuke],
Symmetry-Aware Nonrigid Matching of Incomplete 3D Surfaces,
CVPR14(4193-4200)
IEEE DOI 1409
Nonrigid shape matching; feature descriptor; graph matching BibRef

Xu, W.P.[Wei-Peng], Salzmann, M.[Mathieu], Wang, Y.T.[Yong-Tian], Liu, Y.[Yue],
Deformable 3D Fusion: From Partial Dynamic 3D Observations to Complete 4D Models,
ICCV15(2183-2191)
IEEE DOI 1602
BibRef
Earlier:
Nonrigid Surface Registration and Completion from RGBD Images,
ECCV14(II: 64-79).
Springer DOI 1408
Deformable models BibRef

Kim, B.S.[Byung-Soo], Xu, S.[Shili], Savarese, S.[Silvio],
Accurate Localization of 3D Objects from RGB-D Data Using Segmentation Hypotheses,
CVPR13(3182-3189)
IEEE DOI 1309
3D localization; Object detection; Object recognition; RGB-D BibRef

Shapovalov, R.[Roman], Vetrov, D.[Dmitry], Kohli, P.[Pushmeet],
Spatial Inference Machines,
CVPR13(2985-2992)
IEEE DOI 1309
3D point clouds Interpretation of 3D point clouds. BibRef

Cha, Y.W.[Young-Woon], Lim, H.[Hwasup], Lee, S.O.[Seong-Oh], Kim, H.G.[Hyoung-Gon], Ahn, S.C.[Sang Chul],
Spin Image Revisited: Fast Candidate Selection Using Outlier Forest Search,
CDF12(II:209-222).
Springer DOI 1304
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Maeda, M.[Makoto], Nakamae, T.[Takashi], Inoue, K.[Katsuhiro],
Surface matching by curvature distribution images generated via gaze modeling,
ICPR12(2194-2197).
WWW Link. 1302
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Zhang, Z.Y.[Zhi-Yuan], Ong, S.H.[Sim Heng], Foong, K.[Kelvin],
Improved spin images for 3D surface matching using signed angles,
ICIP12(537-540).
IEEE DOI 1302
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Ren, C.Y.E.[Carl Yuh-Eng], Reid, I.D.[Ian D.],
A Unified Energy Minimization Framework for Model Fitting in Depth,
CDC4CV12(II: 72-82).
Springer DOI 1210
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Wujanz, D.,
Towards Transparent Quality Measures In Surface Based Registration Processes: Effects of Deformation Onto Commercial and Scientific Implementations,
ISPRS12(XXXIX-B5:251-256).
DOI Link 1209
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Biasotti, S.[Silvia],
Shape comparison through mutual distances of real functions,
3DOR10(33-38).
DOI Link 1111
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Halma, A.[Arvid], ter Haar, F.[Frank], Bovenkamp, E.[Ernst], Eendebak, P.[Pieter], van Eekeren, A.[Adam],
Single spin image-ICP matching for efficient 3D object recognition,
3DOR10(21-26).
DOI Link 1111
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Tong, C.[Can], Kamata, S.I.[Sei-Ichiro],
3D object matching based on spherical Hilbert scanning,
ICIP10(2941-2944).
IEEE DOI 1009
BibRef

He, M.Y.[Ming-Yuan], Guan, J.P.[Ji-Ping], Ma, W.M.[Wei-Ming], Shi, W.[Wei],
Satellite Image Positioning Method Based upon Aligning Surface Characteristics,
CISP09(1-5).
IEEE DOI 0910
BibRef

Hermans, J.[Jeroen], Smeets, D.[Dirk], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Robust point set registration using EM-ICP with information-theoretically optimal outlier handling,
CVPR11(2465-2472).
IEEE DOI 1106
BibRef

Smeets, D.[Dirk], Hermans, J.[Jeroen], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Dense shape correspondences using spectral high-order graph matching,
NORDIA11(1-8).
IEEE DOI 1106
BibRef

Smeets, D.[Dirk], Fabry, T.[Thomas], Hermans, J.[Jeroen], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Inelastic Deformation Invariant Modal Representation for Non-rigid 3D Object Recognition,
AMDO10(162-171).
Springer DOI 1007
BibRef
Earlier:
Isometric Deformation Modelling for Object Recognition,
CAIP09(757-765).
Springer DOI 0909
Geodesic distance matrices. BibRef

Li, X.J.[Xin-Ju], Guskov, I.[Igor],
3D object recognition from range images using pyramid matching,
ICCV07(1-6).
IEEE DOI 0710
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Mademlis, A., Daras, P., Tzovaras, D., Strintzis, M.G.,
On 3D Partial Matching of Meaningful Parts,
ICIP07(II: 517-520).
IEEE DOI 0709
BibRef

Germann, M.[Marcel], Breitenstein, M.D.[Michael D.], Park, I.K.[In Kyu], Pfister, H.[Hanspeter],
Automatic Pose Estimation for Range Images on the GPU,
3DIM07(81-90).
IEEE DOI 0708
Shape matching of 3-D modelto range image. BibRef

Gefen, S.[Smadar], Kiryati, N.[Nahum], Bertrand, L.[Louise], Nissanov, J.[Jonathan],
Planar-to-Curved-Surface Image Registration,
MMBIA06(72).
IEEE DOI 0609
BibRef

Smith, W.A.P.[William A.P.], Hancock, E.R.[Edwin R.],
Surface Integration: Two Statistical Approaches,
CIAP07(343-350).
IEEE DOI 0709
BibRef

Fraile, R.[Roberto], Hancock, E.R.[Edwin R.],
Diffusion of Geometric Affinity for Surface Integration,
SSPR06(92-99).
Springer DOI 0608
BibRef
Earlier:
Combinatorial Surface Integration,
ICPR06(I: 59-62).
IEEE DOI 0609

See also Spectral Modes of Facial Needle-Maps. BibRef

Gupta, D., Kumar, A., Daniilidis, K.[Kostas],
Using omnidirectional structure from motion for registration of range images of minimal overlap,
3DPVT04(333-340).
IEEE DOI 0412
BibRef

Frome, A.[Andrea], Huber, D.F.[Daniel F.], Kolluri, R.[Ravi], Bülow, T.[Thomas], Malik, J.[Jitendra],
Recognizing Objects in Range Data Using Regional Point Descriptors,
ECCV04(Vol III: 224-237).
Springer DOI 0405
Region based shape descriptions. Compare to spin images. BibRef

Liu, Y.H.[Yong-Huai], Wei, B.G.[Bao-Gang],
Evaluating structural constraints for accurate range image registration,
3DIM03(187-194).
IEEE DOI 0311
BibRef

Liu, Y.H.[Yong-Huai], Labrosse, F.,
Inverse validation for accurate range image registration with structured data,
ICPR02(III: 537-540).
IEEE DOI 0211
BibRef

Hillenbrand, U.[Ulrich], Hirzinger, G.[Gerd],
Probabilistic Search for Object Segmentation and Recognition,
ECCV02(III: 791 ff.).
Springer DOI 0205
Generative range models. BibRef

Caprara, A., Lancia, G.,
Optimal and near-optimal solutions for 3D structure comparisons,
3DPVT02(737-744).
IEEE DOI 0206
BibRef

Corouge, I., Barillot, C.,
Use of a Probabilistic Shape Model for Non-linear Registration of 3d Scattered Data,
ICIP01(I: 149-152).
IEEE DOI 0108
BibRef

Sistiaga, M., Opderbecke, J., Aldon, M.J.,
Depth image matching for underwater vehicle navigation,
CIAP99(624-629).
IEEE DOI 9909
BibRef

Gabrani, M., Treiak, O.J.,
A novel interpolation problem: surface based matching,
ICIP98(I: 793-797).
IEEE DOI 9810
BibRef

Sim, D.G., Park, R.H.,
Localization Based on the Gradient Information for Dem matching,
MVA98(xx-yy). BibRef 9800

Gennery, D.B.,
Visual Terrain Matching for a Mars Rover,
CVPR89(483-491).
IEEE DOI 3-D is extracted from stereo or other sources and merged through several steps or with aerial data. BibRef 8900

Shu, D.B.[David B.], Li, C.C., and Sun, Y.N.,
An Approach to 3-D Object Identification Using Range Images,
CRA86(118-125). BibRef 8600

Lu, S.W.[Si-Wei], and Wong, A.K.C.[Andrew K.C.],
Analysis of 3-D Scene with Partially Occluded Objects for Robot Vision,
ICPR88(I: 303-308).
IEEE DOI BibRef 8800

Tomita, F., Kanade, T.,
A 3D Vision System: Generating and Matching Shape Descriptions in Range Images,
CAIA84(186-191). BibRef 8400

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