11.2.4 Region Techniques for Range and Surfaces

Hoover, A., Jean-Baptiste, G., Jiang, X.Y., Flynn, P.J., Bunke, H., Goldgof, D.B., Bowyer, K.W., Eggert, D.W., Fitzgibbon, A.W., Fisher, R.B.,
An Experimental Comparison of Range Image Segmentation Algorithms,
PAMI(18), No. 7, July 1996, pp. 673-689.
IEEE DOI 9608
BibRef Edinburgh Evaluation, Range Segmentation. Comparisons. Algorithm UB: (
See also Fast Segmentation of Range Images by Scan Line Grouping. ). Algorithm WSU: (
See also BONSAI: 3D Object Recognition Using Constrained Search. and
See also Segmentation and Classification of Range Images. ). Algorithm USF: (
See also Curvature-Based Approach to Terrain Recognition, A. ). Algorithm UE: No exact reference given, but try: (
See also High-Level CAD Model Acquisition from Range Images. or
See also Experiments in Curvature-Based Segmentation of Range Data. ). Depending on the measure (over/under segmentation, etc.) different ones ranked best. Read this paper first. BibRef

Hoover, A., Jean-Baptiste, G., Goldgof, D., Bowyer, K.W., Flynn, P.J., Jiang, X.Y., Bunke, H.,
Range Image Segmentation: The User's Dilemma,
SCV95(323-328).
IEEE DOI Evaluation, Range Segmentation. Univ. of South Florida. Washington State Univ. Univ. of Bern. Evaluation of segmentation of range into planar patches. BibRef 9500

Jiang, X.Y., Hoover, A., Jean-Baptiste, G., Goldgof, D.B., Bowyer, K.W., Bunke, H.,
A Methodology for Evaluating Edge Detection Techniques for Range Images,
ACCV95(415-419). Hand ground truth data for evaluation. BibRef 9500

Hoover, A., Jean-Baptiste, G., Goldgof, D.B., and Bowyer, K.W.[Kevin W.],
A Methodology for Evaluating Range Image Segmentation Techniques,
WACV94(264-271).
IEEE Abstract. BibRef 9400

Jiang, X., Bowyer, K.W., Morioka, Y., Hiura, S., Sato, K., Inokuchi, S., Bock, M., Guerra, C., Loke, R.E., du Buf, J.M.H.,
Some Further Results of Experimental Comparison of Range Image Segmentation Algorithms,
ICPR00(Vol IV: 877-881).
IEEE DOI 0009
BibRef

Hoffman, R.L.[Richard L.], and Jain, A.K.,
Segmentation and Classification of Range Images,
PAMI(9), No. 5, September 1987, pp. 608-620. BibRef 8709
Earlier: CVPR86(446-451). BibRef
And: MSU-ENGR-86-002, Michigan State Univ, E. Lansing, MI. See the comparison:
See also Experimental Comparison of Range Image Segmentation Algorithms, An. Segment the range image into surface patches, classify the patch, merge compatible patches to produce faces. BibRef

Hoffman, R.L.[Richard L.],
Object Recognition from Range Images,
Ph.D.Department of Computer Science, Michigan State University, 1986. BibRef 8600

Dubes, R.C., Jain, A.K., Nadabar, S.G., and Chen, C.C.,
MRF Model-Based Algorithms for Image Segmentation,
ICPR90(I: 808-814).
IEEE DOI Two level segmentation process. Neighborhoods.
See also Random Field Models in Image Analysis. BibRef 9000

Jain, A.K., and Nadabar, S.G.,
MRF Model-Based Segmentation of Range Images,
ICCV90(667-671).
IEEE DOI BibRef 9000

Hoffman, R., and Jain, A.K.,
Evidence-Based Recognition of 3-D Objects,
PAMI(10), No. 6, November 1988, pp. 783-802.
IEEE DOI BibRef 8811
Earlier:
An Evidence-Based 3D Vision System for Range Images,
ICCV87(521-525). BibRef
Earlier: MSU-ENGR-86-013, Comp Sci Dept Report, 1986. Recognize Range Data. Builds on the description program to recognize the objects. Find notable features, use a rulebase with conditions and weights to compute similarity measure between scene and object. BibRef

Hoffman, R., and Jain, A.K.,
Learning Rules for 3-D Object Recognition,
CVPR88(885-892).
IEEE DOI Rules for the other papers. BibRef 8800

Yokoya, N., and Levine, M.D.,
Volumetric Shapes of Solids of Revolution from a Single-View Range Image,
CVGIP(59), No. 1, January 1994, pp. 43-52.
DOI Link BibRef 9401
Earlier:
Volumetric description of solids of revolution in a range image,
ICPR90(I: 303-308).
IEEE DOI 9006
BibRef

Yokoya, N., and Levine, M.D.,
Range Image Segmentation Based on Differential Geometry: A Hybrid Approach,
PAMI(11), No. 6, June 1989, pp. 643-649.
IEEE DOI BibRef 8906
Earlier:
A Hybrid Approach to Range Image Segmentation,
ICPR88(I: 1-5).
IEEE DOI 8811
Generate surfaces (from range data) using both edge and region information. BibRef

Henderson, T.C.,
Efficient 3-D Object Representations for Industrial Vision Systems,
PAMI(5), No. 6, November 1983, pp. 609-618. BibRef 8311
Earlier:
Efficient Segmentation Method for Range Date,
SPIE(336), Robot Vision, May 1982, pp. 46-47. Region growing to describe 3-D objects by surface patches. BibRef

Liou, S.P., and Jain, R.C.,
An Approach to Three-Dimensional Image Segmentation,
CVGIP(53), No. 3, May 1991, pp. 237-252.
Elsevier DOI BibRef 9105
Earlier:
A Parallel Technique for Three-Dimensional Image Segmentation,
ICPR90(I: 201-203).
IEEE DOI Segmentation is based on 3-D edge detection. This segmentation is applied to spatio-temporal image sequences (slices, or time based).
See also Parallel Technique for Signal-Level Perceptual Organization, A. BibRef

Han, J.H., and Volz, R.A.,
Region Grouping from a Range Image,
CVPR88(241-248).
IEEE DOI Similar to Fan's work. Find convex surface regions and look at the boundaries between them. BibRef 8800

Abdelmalek, N.N.[Nabih N.],
Algebraic Error Analysis for Surface Curvatures and Segmentation of 3-D Range Images,
PR(23), No. 8, 1990, pp. 807-817.
Elsevier DOI BibRef 9000
Earlier:
Algebraic error analysis for surface curvatures of 3-D range images obtained by different methods,
ICPR90(I: 529-534).
IEEE DOI 9006
Segmentation and error analysis for curvature. BibRef

Bhandarkar, S.M.[Suchendra M.], Siebert, A.[Andreas],
Integrating Edge and Surface Information for Range Image Segmentation,
PR(25), No. 9, September 1992, pp. 947-962.
Elsevier DOI BibRef 9209

Parvin, B., and Medioni, G.G.[Gerard G.],
B-rep Object Description from Multiple Range Views,
IJCV(20), No. 1/2, 1996, pp. 81-112. BibRef 9600
Earlier:
B-reps from Unregistered Multiple Range Image,
CRA92(1602-1607). BibRef
Earlier:
Segmentation of Range Images into Planar Surfaces by Split and Merge,
CVPR86(415-417). Use surface normals as the feature for the splitting. An unrelated, though similar, paper is under edge detection in range data.
See also Adaptive Multiscale Feature Extraction from Range Data. BibRef

Strasters, K.C., and Gerbrands, J.J.,
Three-Dimensional Image Segmentation Using a Split, Merge and Group Approach,
PRL(12), No. 5, May 1991, pp. 307-325. BibRef 9105

Strasters, K.C., Smeulders, A.W.M., vander Voort, H.T.M.,
3-D Texture Characterized by Accessibility Measurements, Based on the Grey Weighted Distance Transform,
BioImaging(2), No. 1, 1994, pp. 1-21. BibRef 9400

Hoover, A., Goldgof, D., Bowyer, K.W.,
Extracting a Valid Boundary Representation from a Segmented Range Image,
PAMI(17), No. 9, September 1995, pp. 920-924.
IEEE DOI Line Labels. BibRef 9509

Hoover, A., Goldgof, D., Bowyer, K.W.,
Dynamic-Scale Model Construction From Range Imagery,
PAMI(20), No. 12, December 1998, pp. 1352-1357.
IEEE DOI BibRef 9812

Bose, S.K., Biswas, K.K., Gupta, S.K.,
An Integrated Approach for Range Image Segmentation and Representation,
AIEng(10), No. 3, August 1996, pp. 243-252. 9606
BibRef

Chatterji, G.B., Sridhar, B.,
Discrete Range Clustering Using Monte-Carlo Methods,
SMC-A(26), No. 6, November 1996, pp. 832-837.
IEEE Top Reference. 9611
BibRef

Baccar, M., Gee, L.A., Gonzalez, R.C., Abidi, M.A.,
Segmentation of Range Images Via Data Fusion and Morphological Watersheds,
PR(29), No. 10, October 1996, pp. 1673-1687.
Elsevier DOI Data Fusion. BibRef 9610

Umasuthan, M., Wallace, A.M.,
Outlier Removal and Discontinuity Preserving Smoothing of Range Data,
VISP(143), No. 3, June 1996, pp. 191-200. 9608
Smoothing of range data for segmentattion. BibRef

Wu, M.C., Liu, C.R.,
Analysis of Machined Feature Recognition Techniques Based on B-Rep,
CAD(28), No. 8, August 1996, pp. 603-616. 9607
BibRef

Rimey, R.D., Cohen, F.S.,
A Maximum-Likelihood Approach to Segmenting Range Data,
RA(4), 1988, pp. 277-286. BibRef 8800

Zhao, D.M., Zhang, X.T.,
Range-Data-Based Object Surface Segmentation via Edges and Critical-Points,
IP(6), No. 6, June 1997, pp. 826-830.
IEEE DOI 9705
BibRef

Baccar, M., Gee, L.A., Abidi, M.A.,
Reliable Location and Regression Estimates with Application to Range Image Segmentation,
JMIV(11), No. 3, December 1999, pp. 195-205.
DOI Link BibRef 9912

Köster, K.[Klaus], Spann, M.[Michael],
MIR: An Approach to Robust Clustering-Application to Range Image Segmentation,
PAMI(22), No. 5, May 2000, pp. 430-444.
IEEE DOI 0008
Segmentation, Region Growing. With comparison of results using the method of
See also Experimental Comparison of Range Image Segmentation Algorithms, An. (And the same 4 algorithms used there.) Works better for most cases. Use the Mutual Inlier Ratio (MIR) to compare regions for a region growing algorithm. This reduces impact of outlier points merged into regions. BibRef

Benlamri, R.,
Range image segmentation of scenes with occluded curved objects,
PRL(21), No. 12, November 2000, pp. 1051-1060. 0011
BibRef

Benlamri, R.[Rachid], Al-Marzooqi, Y.[Yousuf],
Free-form object segmentation and representation from registered range and color images,
IVC(22), No. 9, 20 August 2004, pp. 703-717.
Elsevier DOI 0407
BibRef

Werghi, N., Fisher, R.B.[Robert B.], Robertson, C.[Craig], Ashbrook, A.P.,
Faithful recovering of quadric surfaces from 3D range data by global fitting,
ShapeMod(6), No. 1, 2000, pp. 65-78. BibRef 0001 Edinburgh 0001
BibRef
Earlier: A1, A2, A4, A3:
Faithful recovering of quadric surfaces from 3D range data,
3DIM99(280-289).
IEEE DOI BibRef
Earlier: A4, A2, A3, A1:
Finding Surface Correspondence for Object Recognition and Registration Using Pairwise Geometric Histograms,
ECCV98(II: 674).
Springer DOI BibRef Edinburgh BibRef

Robertson, C.[Craig], Fisher, R.B.[Robert B.],
Parallel Evolutionary Registration of Range Data,
CVIU(87), No. 1-3, July 2002, pp. 39-50.
DOI Link 0301
BibRef EdinburghVariation on ICP algorithms. Evolutionary algorithm to avoid local minima. BibRef

Ashbrook, A.P., Fisher, R.B.[Robert B.], Robertson, C.[Craig], Werghi, N.,
Construction of Articulated Models from Range Data,
BMVC99(183-192),
PDF File. BibRef 9900 Edinburgh BibRef
Earlier:
Segmentation of Range Data into Rigid Subsets Using Surface Patches,
ICCV98(201-206).
IEEE DOI BibRef
Earlier:
Segmentation of Range Data into Rigid Subsets using Planar Surface Patches,
BMVC97(530-539). BibRef Edinburgh
HTML Version. Or
PS File. Range data segmentation, automatic 3D shape model acquisition BibRef

Ashbrook, A.P., Fisher, R.B.,
Segmentation of Range Data for the Automatic Construction of Models of Articulated Objects,
Non-Rigid97(xx-yy). BibRef 9700 Edinburgh BibRef

Revol-Muller, C.[Chantal], Peyrin, F.[Francoise], Carrillon, Y.[Yannick], Odet, C.[Christophe],
Automated 3D region growing algorithm based on an assessment function,
PRL(23), No. 1-3, January 2002, pp. 137-150.
Elsevier DOI 0201
BibRef

Revol-Muller, C.,
Automated 3d Region Growing Algorithm Governed by an Evaluation Function,
ICIP00(Vol III: 440-443).
IEEE DOI 0008
BibRef

Bellon, O.R.P.[Olga Regina Pereira], Silva, L.[Luciano],
New improvements to range image segmentation by edge detection,
SPLetters(9), No. 2, February 2002, pp. 43-45.
IEEE Top Reference. 0204

See also Precision Range Image Registration Using a Robust Surface Interpenetration Measure and Enhanced Genetic Algorithms. BibRef

Bellon, O.R.P.[Olga Regina Pereira], Direne, A.I.[Alexandre Ibrahim], Silva, L.[Luciano],
Building meaningful edge maps from range images,
CIAP99(227-228).
IEEE DOI 9909
BibRef
And:
Edge Detection To Guide Range Image Segmentation By Clustering Techniques,
ICIP99(II:725-729).
IEEE DOI BibRef

Gotardo, P.F.U., Bellon, O.R.P., Silva, L.,
Range image segmentation by surface extraction using an improved robust estimator,
CVPR03(II: 33-38).
IEEE DOI 0307
BibRef
Earlier: A3, A2, A1:
A global-to-local approach for robust range image segmentation,
ICIP02(I: 773-776).
IEEE DOI 0210
BibRef
Earlier: A3, A2, A1:
Edge-based Image Segmentation Using Curvature Sign Maps from Reflectance and Range Images,
ICIP01(I: 730-733).
IEEE DOI 0108
BibRef

Bellon, O.R.P.[Olga R. P.], Tozzi, C.L.[Clesio L.],
An integrated approach for segmentation and representation of range images,
CIAP97(I: 279-286).
Springer DOI 9709
BibRef

Vrubel, A.[Alexandre], Bellon, O.R.P.[Olga R.P.], Silva, L.[Luciano],
Planar background elimination in range images: A practical approach,
ICIP09(3197-3200).
IEEE DOI 0911
BibRef

Esedoglu, S.[Selim], March, R.[Riccardo],
Segmentation with Depth but Without Detecting Junctions,
JMIV(18), No. 1, January 2003, pp. 7-15.
DOI Link 0301
BibRef

Khalifa, I.[Inas], Moussa, M.[Medhat], Kamel, M.[Mohamed],
Range image segmentation using local approximation of scan lines with application to CAD model acquisition,
MVA(13), No. 5-6, 2003, pp. 263-274.
WWW Link. 0304
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Khalifa, I.,
Range Image Segmentation with Application to CAD Model Acquisition,
ICIP00(Vol II: 740-743).
IEEE DOI 0008
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Damiand, G.[Guillaume], Resch, P.[Patrick],
Split-and-merge algorithms defined on topological maps for 3D image segmentation,
GM(65), No. 1-3, May 2003, pp. 149-167.
Elsevier DOI 0309

See also Topological Model for Two-Dimensional Image Representation: Definition and Optimal Extraction Algorithm. BibRef

Damiand, G.[Guillaume],
Topological Model for 3D Image Representation: Definition and Incremental Extraction Algorithm,
CVIU(109), No. 3, March 2008, pp. 260-289.
Elsevier DOI 0802
Topological model; 3D image representation; Intervoxel boundaries; Combinatorial map; Structure for image processing BibRef

Damiand, G.[Guillaume], Dupas, A.[Alexandre], Lachaud, J.O.[Jacques-Olivier],
Fully deformable 3D digital partition model with topological control,
PRL(32), No. 9, 1 July 2011, pp. 1374-1383.
Elsevier DOI 1101
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Combining Topological Maps, Multi-Label Simple Points, and Minimum-Length Polygons for Efficient Digital Partition Model,
IWCIA11(56-69).
Springer DOI 1105
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Earlier: A2, A1, A3:
Multi-Label Simple Points Definition for 3D Images Digital Deformable Model,
DGCI09(156-167).
Springer DOI 0909
3D image segmentation; Simple point; Deformable model; Intervoxel boundaries; Multi-label image; Cubical complexes BibRef

Dupas, A.[Alexandre], Damiand, G.[Guillaume],
Comparison of Local and Global Region Merging in the Topological Map,
IWCIA08(xx-yy).
Springer DOI 0804
BibRef
And:
First Results for 3D Image Segmentation with Topological Map,
DGCI08(xx-yy).
Springer DOI 0804
BibRef

Cuel, L.[Louis], Lachaud, J.O.[Jacques-Olivier], Mérigot, Q.[Quentin], Thibert, B.[Boris],
Robust Geometry Estimation Using the Generalized Voronoi Covariance Measure,
SIIMS(8), No. 2, 2015, pp. 1293-1314.
DOI Link 1507
BibRef
Earlier: A1, A2, A4, Only:
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DGCI14(134-149).
Springer DOI 1410
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Lachaud, J.O.[Jacques-Olivier], Thibert, B.[Boris],
Properties of Gauss Digitized Shapes and Digital Surface Integration,
JMIV(54), No. 2, February 2016, pp. 162-180.
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Damiand, G.[Guillaume], Peltier, S.[Samuel], Fuchs, L.[Laurent], Lienhardt, P.[Pascal],
Topological Map: An Efficient Tool to Compute Incrementally Topological Features on 3D Images,
IWCIA06(1-15).
Springer DOI 0606
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Grasset-Simon, C.[Carine], Damiand, G.[Guillaume], Lienhardt, P.[Pascal],
nD generalized map pyramids: Definition, representations and basic operations,
PR(39), No. 4, April 2006, pp. 527-538.
Elsevier DOI Irregular pyramid; Hierarchical data structure; Pyramid of generalized maps; Multi-level segmented image 0604

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Wang, X.[Xiao], Wang, H.[Han],
Markov random field modeled range image segmentation,
PRL(25), No. 3, February 2004, pp. 367-375.
Elsevier DOI 0401
BibRef
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Evolutionary gibbs sampler for image segmentation,
ICIP04(V: 3479-3482).
IEEE DOI 0505
BibRef
And:
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ICARCV04(I: 98-102).
IEEE DOI 0412
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Wang, H.Z.[Han-Zi], Suter, D.[David],
Robust Adaptive-Scale Parametric Model Estimation for Computer Vision,
PAMI(26), No. 11, November 2004, pp. 1459-1474.
IEEE Abstract. 0410
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Earlier:
Robust Fitting by Adaptive-Scale Residual Consensus,
ECCV04(Vol III: 107-118).
Springer DOI 0405
Robust model fitting, estimate parameters, estimatte noise. Determine inliers and outliers. Adaptive-Scale Residual Consensus (ASRC). Robust to highly corrupted data. Compare to RANSAC (
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Wang, H.Z.[Han-Zi], Suter, D.[David],
MDPE: A Very Robust Estimator for Model Fitting and Range Image Segmentation,
IJCV(59), No. 2, September 2004, pp. 139-166.
DOI Link 0404
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Wang, H.Z.[Han-Zi], Chin, T.J.[Tat-Jun], Suter, D.[David],
Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers,
PAMI(34), No. 6, June 2012, pp. 1177-1192.
IEEE DOI 1205
Robust datafitting. Segment multiple structure data with outliers. Apply to linefitting, circle fitting, range image segmentation, homography estimation, motion segmentation. BibRef

Yu, J.[Jin], Eriksson, A.P.[Anders P.], Chin, T.J.[Tat-Jun], Suter, D.[David],
An Adversarial Optimization Approach to Efficient Outlier Removal,
JMIV(48), No. 3, March 2014, pp. 451-466.
Springer DOI 1403
BibRef
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IEEE DOI 1201
BibRef

Chin, T.J.[Tat-Jun], Kee, Y.H.[Yang Heng], Eriksson, A.P.[Anders P.], Neumann, F.[Frank],
Guaranteed Outlier Removal with Mixed Integer Linear Programs,
CVPR16(5858-5866)
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Wong, H.S.[Hoi Sim], Chin, T.J.[Tat-Jun], Yu, J.[Jin], Suter, D.[David],
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Elsevier DOI 1310
Robust model fitting BibRef

Pham, T.T.[Trung Thanh], Chin, T.J.[Tat-Jun], Yu, J.[Jin], Suter, D.[David],
The Random Cluster Model for Robust Geometric Fitting,
PAMI(36), No. 8, August 2014, pp. 1658-1671.
IEEE DOI 1407
BibRef
Earlier: CVPR12(710-717).
IEEE DOI 1208
Accuracy BibRef

Pham, T.T.[Trung Thanh], Chin, T.J.[Tat-Jun], Schindler, K., Suter, D.[David],
Interacting Geometric Priors For Robust Multimodel Fitting,
IP(23), No. 10, October 2014, pp. 4601-4610.
IEEE DOI 1410
Complexity theory BibRef

Xiao, G.B.[Guo-Bao], Wang, H.Z.[Han-Zi], Lai, T.T.[Tao-Tao], Suter, D.[David],
Hypergraph modelling for geometric model fitting,
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Elsevier DOI 1609
Hypergraph modelling BibRef

Xiao, G.B.[Guo-Bao], Wang, H.Z.[Han-Zi], Ma, J.Y.[Jia-Yi], Suter, D.[David],
Segmentation by Continuous Latent Semantic Analysis for Multi-Structure Model Fitting,
IJCV(129), No. 7, July 2021, pp. 2034-2056. 2106
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Xiao, G.B.[Guo-Bao], Wang, H.Z.[Han-Zi], Yan, Y.[Yan], Zhang, L.M.[Li-Ming],
Mode seeking on graphs for geometric model fitting via preference analysis,
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Elsevier DOI 1609
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Wang, X.[Xing], Xiao, G.B.[Guo-Bao], Yan, Y.[Yan], Wang, H.Z.[Han-Zi],
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Springer DOI 1704
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Wang, H.Z.[Han-Zi], Xiao, G.B.[Guo-Bao], Yan, Y.[Yan], Suter, D.[David],
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IEEE DOI 1902
Data models, Computational modeling, Robustness, Fitting, Computational complexity, Analytical models, multi-structure data BibRef

Xiao, G.B.[Guo-Bao], Wang, H.Z.[Han-Zi], Yan, Y.[Yan], Suter, D.[David],
Superpixel-Guided Two-View Deterministic Geometric Model Fitting,
IJCV(127), No. 4, April 2019, pp. 323-339.
Springer DOI 1903
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Earlier:
Superpixel-Based Two-View Deterministic Fitting for Multiple-Structure Data,
ECCV16(VI: 517-533).
Springer DOI 1611
BibRef
Earlier: A2, A1, A3, A4:
Mode-Seeking on Hypergraphs for Robust Geometric Model Fitting,
ICCV15(2902-2910)
IEEE DOI 1602
Computational modeling BibRef

Wong, H.S.[Hoi Sim], Chin, T.J.[Tat-Jun], Yu, J.[Jin], Suter, D.[David],
Mode seeking over permutations for rapid geometric model fitting,
PR(46), No. 1, January 2013, pp. 257-271.
Elsevier DOI 1209
BibRef
Earlier:
Dynamic and hierarchical multi-structure geometric model fitting,
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IEEE DOI 1201
Geometric model fitting; Hypothesis sampling; Multi-structure data; Mode seeking over permutations BibRef

Yu, J.[Jin], Chin, T.J.[Tat-Jun], Suter, D.[David],
A global optimization approach to robust multi-model fitting,
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IEEE DOI 1106
BibRef

Chin, T.J.[Tat-Jun], Wang, H.Z.[Han-Zi], Suter, D.[David],
Robust fitting of multiple structures: The statistical learning approach,
ICCV09(413-420).
IEEE DOI 0909
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Multi-scale Conditional Random Fields for over-segmented irregular 3D point clouds classification,
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IEEE DOI 0806
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Range Image Segmentation by an Effective Jump-Diffusion Method,
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IEEE Abstract. 0409
BibRef
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A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction,
ECCV02(III: 502 ff.).
Springer DOI 0205
Range image and reflectance map into surfaces. BibRef

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Range image segmentation based on randomized Hough transform,
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Elsevier DOI 0509
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Monga, O.[Olivier],
Defining and computing stable representations of volume shapes from discrete trace using volume primitives: Application to 3D image analysis in soil science,
IVC(25), No. 7, 1 July 2007, pp. 1134-1153.
Elsevier DOI 0705
3D segmentation; Volume approximation; 3D volume image; Computed tomography; Soil images; Functional minimization BibRef

Jin, H.L.[Hai-Lin], Yezzi, A.J.[Anthony J.], Soatto, S.[Stefano],
Mumford-Shah on the Move: Region-Based Segmentation on Deforming Manifolds with Application to 3-D Reconstruction of Shape and Appearance from Multi-View Images,
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Springer DOI 0712
BibRef
Earlier:
Region-Based Segmentation on Evolving Surfaces with Application to 3D Reconstruction of Shape and Piecewise Constant Radiance,
ECCV04(Vol II: 114-125).
Springer DOI 0405

See also Multi-View Stereo Reconstruction of Dense Shape and Complex Appearance. BibRef

Djebali, M., Melkemi, M., Melkemi, K., Sapidis, N.,
Coiflet Based Methods For Range Image Processing,
IJIG(7), No. 2, April 2007, pp. 321-351. 0704
BibRef

Djebali, M.[Mourad], Melkemi, K., Melkemi, M., Vandorpe, D.,
Range Image Processing Based on Multiresolution Analysis,
ICIP96(I: 281-286).
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Earlier:
Coiflets for Range Image Segmentation,
ICPR96(B81.7). 9608
(Univ. Claude Bernard Lyon1, F) BibRef

Djebali, M., Melkemi, M., Vandorpe, D.,
3-D range images segmentation based on Deriche's optimum filters,
ICIP94(III: 503-507).
IEEE DOI 9411
BibRef

Holdstein, Y., Fischer, A.,
Three-dimensional surface reconstruction using meshing growing neural gas (MGNG),
VC(24), No. 4, April 2008, pp. xx-yy.
Springer DOI 0804
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Heitz, G.[Geremy], Elidan, G.[Gal], Packer, B.[Benjamin], Koller, D.[Daphne],
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IJCV(84), No. 1, August 2009, pp. xx-yy.
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LOOPS method to learn deformable shape models. BibRef

Heitz, G.[Geremy], Koller, D.[Daphne],
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ECCV08(I: 30-43).
Springer DOI 0810
Award, ECCV. BibRef

Elidan, G.[Gal], Heitz, G.[Geremy], Koller, D.[Daphne],
Learning Object Shape: From Drawings to Images,
CVPR06(II: 2064-2071).
IEEE DOI 0606
Landmark based piecewise linear shape. BibRef

Anguelov, D.[Dragomir], Taskar, B.[Ben], Chatalbashev, V.[Vassil], Koller, D.[Daphne], Gupta, D.[Dinkar], Heitz, G.[Geremy], Ng, A.[Andrew],
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data,
CVPR05(II: 169-176).
IEEE DOI 0507
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Bergamasco, F.[Filippo], Albarelli, A.[Andrea], Torsello, A.[Andrea],
A graph-based technique for semi-supervised segmentation of 3D surfaces,
PRL(33), No. 15, 1 November 2012, pp. 2057-2064.
Elsevier DOI 1210
BibRef
Earlier:
Semi-supervised Segmentation of 3D Surfaces Using a Weighted Graph Representation,
GbRPR11(225-234).
Springer DOI 1105

See also Fast 3D surface reconstruction by unambiguous compound phase coding. 3D segmentation; Directional curvature metric; Greedy label propagation BibRef

Siddiqui, J.R.[J. Rafid], Havaei, M.[Mohammad], Khatibi, S.[Siamak], Lindley, C.A.[Craig A.],
A novel plane extraction approach using supervised learning,
MVA(24), No. 6, August 2013, pp. 1229-1237.
Springer DOI 1307
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Habib, A.[Ayman], Lin, Y.J.[Yun-Jou],
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Incremental reconstruction of planar B-Rep models from multiple point clouds,
VC(32), No. 6-8, June 2016, pp. 945-954.
WWW Link. 1608
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Lee, S.K.[Seung-Kyu], Kim, J.[Jungjun], Lim, H.[Hwasup], Ahn, S.C.[Sang Chul],
Surface reflectance estimation and segmentation from single depth image of ToF camera,
SP:IC(47), No. 1, 2016, pp. 452-462.
Elsevier DOI 1610
Material imaging BibRef

Ni, H.[Huan], Lin, X.G.[Xiang-Guo], Zhang, J.X.[Ji-Xian],
Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests,
RS(9), No. 3, 2017, pp. xx-yy.
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Airborne laser scanning. BibRef

Wang, L.[Li], Tang, X.A.[Xiao-An], Zhang, J.[Junda], Guan, D.D.[Dong-Dong],
A Hybrid Approach via SRG and IDE for Volume Segmentation,
IEICE(E100-D), No. 9, September 2017, pp. 2257-2260.
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Symmetric Region Growing (SRG) and Information Diffusion Estimation (IDE). BibRef

Wang, L.[Li], Tang, X.A.[Xiao-An], Zhang, J.[Junda], Guan, D.D.[Dong-Dong],
Statistical Property Guided Feature Extraction for Volume Data,
IEICE(E101-D), No. 1, January 2018, pp. 261-264.
WWW Link. 1801
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Shin, M.O., Oh, G.M., Kim, S.W., Seo, S.W.,
Real-Time and Accurate Segmentation of 3-D Point Clouds Based on Gaussian Process Regression,
ITS(18), No. 12, December 2017, pp. 3363-3377.
IEEE DOI 1712
Clustering algorithms, Gaussian processes, Laser radar, Real-time systems, Roads, real-time segmentation BibRef

Choi, G.P.T.[Gary P. T.], Rycroft, C.H.[Chris H.],
Density-Equalizing Maps for Simply Connected Open Surfaces,
SIIMS(11), No. 2, 2018, pp. 1134-1178.
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Sureface segmentation. BibRef

Lyu, Z.Y.[Zhi-Yuan], Choi, G.P.T.[Gary P. T.], Lui, L.M.[Lok Ming],
Bijective Density-Equalizing Quasiconformal Map for Multiply Connected Open Surfaces,
SIIMS(17), No. 1, 2024, pp. 706-755.
DOI Link 2404
BibRef

Che, E.[Erzhuo], Olsen, M.J.[Michael J.],
Multi-scan segmentation of terrestrial laser scanning data based on normal variation analysis,
PandRS(143), 2018, pp. 233-248.
Elsevier DOI 1808
Terrestrial Laser Scanning, Lidar, Segmentation, Edge detection, Region growing, Feature extraction BibRef

Che, E.[Erzhuo], Olsen, M.J.[Michael J.],
An Efficient Framework for Mobile Lidar Trajectory Reconstruction and Mo-norvana Segmentation,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
Lidar processing by trajectory reconstruction, scan pattern grid generation, and Mo-norvana (Mobile Normal Variation Analysis) segmentation. BibRef

Tachella, J.[Julián], Altmann, Y.[Yoann], Ren, X.M.[Xi-Ming], McCarthy, A.[Aongus], Buller, G.S.[Gerald S.], McLaughlin, S.[Stephen], Tourneret, J.Y.[Jean-Yves],
Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data,
SIIMS(12), No. 1, 2019, pp. 521-550.
DOI Link 1904
Low light, low photon, Lidar. BibRef

Li, Y.[Yuan], Wu, B.[Bo], Ge, X.M.[Xu-Ming],
Structural segmentation and classification of mobile laser scanning point clouds with large variations in point density,
PandRS(153), 2019, pp. 151-165.
Elsevier DOI 1906
Mobile laser scanning, Point cloud, Segmentation, Classification, Varying point density BibRef

Yang, B.[Bo], Rosa, S.[Stefano], Markham, A.[Andrew], Trigoni, N.[Niki], Wen, H.K.[Hong-Kai],
Dense 3D Object Reconstruction from a Single Depth View,
PAMI(41), No. 12, December 2019, pp. 2820-2834.
IEEE DOI 1911
Image reconstruction, Solid modeling, Periodic structures, Generative adversarial networks, conditional GAN BibRef

Yang, B.[Bo], Lai, Z.H.[Zi-Hang], Lu, X.X.[Xiao-Xuan], Lin, S.Y.[Shu-Yu], Wen, H.K.[Hong-Kai], Markham, A.[Andrew], Trigoni, N.[Niki],
Learning 3D Scene Semantics and Structure from a Single Depth Image,
DeepSLAM18(422-4223)
IEEE DOI 1812
Shape, Semantics, Image reconstruction, Image segmentation, Feature extraction, Periodic structures BibRef

Yang, B.[Bo], Wang, S.[Sen], Markham, A.[Andrew], Trigoni, N.[Niki],
Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction,
IJCV(128), No. 1, January 2020, pp. 53-73.
Springer DOI 2002
BibRef

Yang, B.[Bo], Wen, H.K.[Hong-Kai], Wang, S.[Sen], Clark, R.[Ronald], Markham, A.[Andrew], Trigoni, N.[Niki],
3D Object Reconstruction from a Single Depth View with Adversarial Learning,
3DSemantics17(679-688)
IEEE DOI 1802
Image reconstruction, Shape, Solid modeling, Training BibRef

Yu, Q.H.[Qi-Hang], Yang, D.[Dong], Roth, H.[Holger], Bai, Y.T.[Yu-Tong], Zhang, Y.X.[Yi-Xiao], Yuille, A.L.[Alan L.], Xu, D.G.[Da-Guang],
C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation,
CVPR20(4125-4134)
IEEE DOI 2008
Network topology, Biomedical imaging, Image segmentation, Topology BibRef

Zhu, Z.T.[Zhuo-Tun], Liu, C.X.[Chen-Xi], Yang, D.[Dong], Yuille, A.L.[Alan L.], Xu, D.G.[Da-Guang],
V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation,
3DV19(240-248)
IEEE DOI 1911
Decoding, Image segmentation, Neural Architecture Search BibRef

Liu, C.X.[Chen-Xi], Chen, L.C.[Liang-Chieh], Schroff, F.[Florian], Adam, H.[Hartwig], Hua, W.[Wei], Yuille, A.L.[Alan L.], Fei-Fei, L.[Li],
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation,
CVPR19(82-92).
IEEE DOI 2002
BibRef

Drees, D.[Dominik], Eilers, F.[Florian], Jiang, X.Y.[Xiao-Yi],
Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Images,
IP(31), 2022, pp. 4431-4446.
IEEE DOI 2207
Image segmentation, Octrees, Memory management, Biomedical imaging, Image resolution, Voltage, Volume segmentation, random walk BibRef

Lai, B.K.[Bao-Kang], Yuan, Y.T.[Ying-Tao], Zhang, Y.Q.[Yue-Qiang], Hu, B.[Biao], Yu, Q.F.[Qi-Feng],
An Accurate and Efficient Supervoxel Re-Segmentation Approach for Large-Scale Point Clouds Using Plane Constraints,
RS(15), No. 16, 2023, pp. 3973.
DOI Link 2309
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Wang, R.B.[Rui-Bin], Ying, X.H.[Xiang-Hua], Xing, B.[Bowei], Tong, X.[Xin], Chen, T.Y.[Tai-Yan], Yang, J.[Jinfa], Shi, Y.J.[Yong-Jie],
Improving point cloud classification and segmentation via parametric veronese mapping,
PR(144), 2023, pp. 109784.
Elsevier DOI 2310
3D Point cloud, Deep learning, Non-linear space mapping, Shape classification, Part segmentation, Semantic segmentation BibRef

Axelsson, M.[Maria], Holmberg, M.[Max], Serra, S.[Sabina], Ovrén, H.[Hannes], Tulldahl, M.[Michael],
Semantic labeling of LIDAR point clouds for UAV applications,
PBVS21(4309-4316)
IEEE DOI 2109
Training, Laser radar, Image color analysis, Semantics, Measurement by laser beam, Vegetation mapping BibRef

Li, J.X.[Jia-Xin], Chen, B.M.[Ben M.], Lee, G.H.[Gim Hee],
SO-Net: Self-Organizing Network for Point Cloud Analysis,
CVPR18(9397-9406)
IEEE DOI 1812
Feature extraction, Training, Shape, Graphical models BibRef

Chen, D.Z.Y.[Dave Zhen-Yu], Chang, A.X.[Angel X.], Nießner, M.[Matthias],
Scanrefer: 3d Object Localization in RGB-D Scans Using Natural Language,
ECCV20(XX:202-221).
Springer DOI 2011
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Lyu, Y., Huang, X., Zhang, Z.,
Learning to Segment 3D Point Clouds in 2D Image Space,
CVPR20(12252-12261)
IEEE DOI 2008
Image segmentation, Laser radar, Feature extraction, Layout, Image representation BibRef

Boubou, S.[Soma], Narikiyo, T.[Tatsuo], Kawanishi, M.[Michihiro],
A Hierarchical Segmentation Approach with Convolution-Recursive Deep Learning for 3D Multi-Object Recognition under Partial Occlusion Conditions,
MVA19(1-6)
DOI Link 1911
image segmentation, learning (artificial intelligence), neural nets, object recognition, Surface treatment BibRef

Sharma, G.[Gopal], Kalogerakis, E.[Evangelos], Maji, S.[Subhransu],
Learning Point Embeddings from Shape Repositories for Few-Shot Segmentation,
3DV19(67-75)
IEEE DOI 1911
Learning surfaces, primitives and connection. Shape, Metadata, Semantics, Measurement, Solid modeling, Training, Few Shot Segmentation, Point Network BibRef

Kozlov, C., Slavcheva, M., Ilic, S.,
Patch-Based Non-rigid 3D Reconstruction from a Single Depth Stream,
3DV18(42-51)
IEEE DOI 1812
expectation-maximisation algorithm, image reconstruction, image registration, image representation, image segmentation, Monocular Reconstruction BibRef

Zong, Z., Chen, C., Mi, X., Sun, W., Song, Y., Li, J., Dong, Z., Huang, R., Yang, B.,
A Deep Learning Approach for Urban Underground Objects Detection From Vehicle-borne Ground Penetrating Radar Data in Real-Time,
PIA19(293-299).
DOI Link 1912
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Huang, Q., Wang, W., Neumann, U.,
Recurrent Slice Networks for 3D Segmentation of Point Clouds,
CVPR18(2626-2635)
IEEE DOI 1812
Task analysis, Semantics, Shape, Feature extraction, Silicon BibRef

Beloborodov, D., Mestetskiy, L.,
Foreground Detection On Depth Maps Using Skeletal Representation Of Object Silhouettes,
PTVSBB17(7-11).
DOI Link 1805
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Wu, Y.J.[Yun-Jie], Sun, Z.X.[Zheng-Xing], Song, Y.C.[You-Cheng], Li, H.Y.[Hong-Yan],
ShapeCreator: 3D Shape Generation from Isomorphic Datasets Based on Autoencoder,
MMMod18(II:264-276).
Springer DOI 1802
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Lin, Y.,
Hierarchical co-segmentation of 3D point clouds for indoor scene,
WSSIP17(1-5)
IEEE DOI 1707
Geometry, Image color analysis, Mathematical model, Principal component analysis, Silicon, clustering, co-segmentation, hierarchy BibRef

Morris, D.[Daniel], Imran, S.[Saif], Chen, J.[Jin], Kramer, D.[David],
Growing Depth Image Superpixels for Foliage Modeling,
CRV16(406-409)
IEEE DOI 1612
Superpixels. Segment depth images without color. BibRef

Sakou, L.B.[Lionel B.], Wilches, D.[Daniel], Banic, A.[Amy],
Region Growing Selection Technique for Dense Volume Visualization,
ISVC15(II: 745-754).
Springer DOI 1601
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Veitch-Michaelis, J., Muller, J.P., Storey, J., Walton, D., Foster, M.,
Data Fusion of Lidar into a Region Growing Stereo Algorithm,
Seamless15(107-112).
DOI Link 1508
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Liu, T.L.[Tyng-Luh], Chang, K.Y.[Kai-Yueh], Lai, S.H.[Shang-Hong],
Exploring Depth Information for Object Segmentation and Detection,
ICPR14(4340-4345)
IEEE DOI 1412
Databases BibRef

Dutta, A., Engels, J., Hahn, M.,
A Distance-Weighted Graph-Cut Method for the Segmentation of Laser Point Clouds,
PCV14(81-88).
DOI Link 1404
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Pirovano, M.[Michele], Ren, C.Y.H.[Carl Yu-Heng],
Robust Silhouette Extraction from Kinect Data,
CIAP13(I:642-651).
Springer DOI 1311
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Mahabadi, R.K.[Rabeeh Karimi], Hane, C.[Christian], Pollefeys, M.[Marc],
Segment based 3D object shape priors,
CVPR15(2838-2846)
IEEE DOI 1510
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Dorea, C.[Camilo], de Queiroz, R.L.[Ricardo L.],
Depth map reconstruction using color-based region merging,
ICIP11(1977-1980).
IEEE DOI 1201
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Aubry, M.[Mathieu], Schlickewei, U.[Ulrich], Cremers, D.[Daniel],
The wave kernel signature: A quantum mechanical approach to shape analysis,
4DMOD11(1626-1633).
IEEE DOI 1201
BibRef
And:
Pose-Consistent 3D Shape Segmentation Based on a Quantum Mechanical Feature Descriptor,
DAGM11(122-131).
Springer DOI 1109
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Mutto, C.D.[C. Dal], Zanuttigh, P.[Pietro], Cortelazzo, G.M.[Guido M.], Mattoccia, S.,
Scene Segmentation Assisted by Stereo Vision,
3DIMPVT11(57-64).
IEEE DOI 1109
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Lari, Z.[Zahra], Habib, A.F.[Ayman F.],
A New Approach for Segmentation-Based Texturing of Laser Scanning Data,
3D-Arch15(115-121).
DOI Link 1504
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Lari, Z.[Zahra], Habib, A.F.[Ayman F.], Kwak, E.[Eunju],
An Adaptive Approach for Segmentation of 3D Laser Point Cloud,
Laser11(xx-yy).
DOI Link 1109
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Krauß, T., d'Angelo, P.,
Morphological filling of digital elevation models,
HighRes11(xx-yy).
PDF File. 1106
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Cao, Y.[Yang], Xia, Y.[Yan], Wang, Z.F.[Zeng-Fu],
A Close-Form Iterative Algorithm for Depth Inferring from a Single Image,
ECCV10(V: 729-742).
Springer DOI 1009
Segmentation, infer relative region depths, region merging using depths. BibRef

Bleyer, M.[Michael], Rother, C.[Carsten], Kohli, P.[Pushmeet],
Surface stereo with soft segmentation,
CVPR10(1570-1577).
IEEE DOI 1006
The scene is a few smooth surfaces. Similar pixels likely on same 3D surface. BibRef

Bayramoglu, N.[Neslihan], Alatan, A.A.[A. Aydin],
Shape Index SIFT: Range Image Recognition Using Local Features,
ICPR10(352-355).
IEEE DOI 1008
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Kim, V.G.[Vladimir G.], Li, W., Mitra, N.J., di Verdi, S., Funkhouser, T.[Thomas],
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Golovinskiy, A.[Aleksey], Kim, V.G.[Vladimir G.], Funkhouser, T.[Thomas],
Shape-based recognition of 3D point clouds in urban environments,
ICCV09(2154-2161).
IEEE DOI 0909
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Golovinskiy, A.[Aleksey], Funkhouser, T.[Thomas],
Min-cut based segmentation of point clouds,
S3DV09(39-46).
IEEE DOI 0910
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Sabov, A., Kruger, J.,
Segmentation of 3D points from range camera data using scanlines,
WSSIP08(429-432).
IEEE DOI 0806
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Alshawabkeh, Y.[Yahya], Haala, N.[Norbert], Fritsch, D.[Dieter],
Range Image Segmentation Using the Numerical Description of the Mean Curvature Values,
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Huang, X.F.[Xian-Feng], Cheng, X.G.[Xiao-Guang], Zhang, F.[Fan], Gong, J.Y.[Jian-Ya],
Side Ratio Constrain Based Precise Boundary Tracing Algorithm for Discrete Point Clouds,
ISPRS08(B3b: 349 ff).
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Luo, D.A.[De-An], Wang, Y.M.[Yan-Min],
Rapid Extracting Pillars by Slicing Point Clouds,
ISPRS08(B3b: 215 ff).
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Springer DOI 0706
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ICIP07(I: 53-56).
IEEE DOI 0709
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Boulanger, P., Osorio, G., Prieto, F.,
Hierarchical segmentation of range images with contour constraints,
3DIM05(278-284).
IEEE DOI 0508
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Wei, Y.[Yi], Hu, S.[Shushu], Li, Y.[Yu],
Data Segmentation of Stereo Images with Complicated Background,
ICIAR07(263-270).
Springer DOI 0708
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Peters, G.[Gabriele], Kerdels, J.[Jochen],
Image Segmentation Based on Height Maps,
CAIP07(612-619).
Springer DOI 0708
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Buatois, L.[Luc], Caumon, G.[Guillaume], Lévy, B.[Bruno],
GPU Accelerated Isosurface Extraction on Tetrahedral Grids,
ISVC06(I: 383-392).
Springer DOI 0611
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Yang, X.Q.[Xing-Qiang], Zhang, C.M.[Cai-Ming],
GLOBAL Topology Preservation in Isosurface Extraction of Volumetric Data,
ISVC06(II: 344-353).
Springer DOI 0611
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Yan, D.M.[Dong-Ming], Liu, Y.[Yang], Wang, W.P.[Wen-Ping],
Quadric Surface Extraction by Variational Shape Approximation,
GMP06(73-86).
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Rabbani, T., van den Heuvel, F.A., Vosselman, G.[George],
Segmentation of point clouds using smoothness constraint,
IEVM06(xx-yy).
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Rabbani, T., van den Heuvel, F.A.,
Efficient Hough transform for automatic detection of cylinders in point clouds,
Laser05(xx-yy).
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Bretar, F., Roux, M.,
Hybrid image segmentation using LiDAR 3D planar primitives,
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Gachter, S.[Stefan], Nguyen, V.[Viet], Siegwart, R.[Roland],
Results on Range Image Segmentation for Service Robots,
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Plane extraction using lines. BibRef

Osorio, G.[Gustavo], Boulanger, P.[Pierre], Prieto, F.[Flavio],
An Experimental Comparison of a Hierarchical Range Image Segmentation Algorithm,
CRV05(571-578).
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Boulanger, P.,
Simultaneous segmentation of range and color images based on Bayesian decision theory,
CRV04(58-63).
IEEE DOI 0408
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Boulanger, P.[Pierre], Jokinen, O.[Olli], Beraldin, J.A.[J. Angelo],
Intrinsic Filtering of Range Images Using a Physically Based Noise Model,
VI02(320).
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Kim, N.H., Park, J.S.[Jai Song],
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ICIP04(I: 231-234).
IEEE DOI 0505
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Brisc, F.,
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Southwest04(114-118).
IEEE DOI 0411
Volumetric reconstruction, user controls detail level. BibRef

Maeda, M., Kumamaru, K., Inoue, K.,
Segmentation of range data based on a stochastic clustering method with competitive process,
ICPR04(I: 624-627).
IEEE DOI 0409
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Xiang, R.H.[Ri-Hua], Wang, R.S.[Run-Sheng],
Range image segmentation based on split-merge clustering,
ICPR04(III: 614-617).
IEEE DOI 0409
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Taillandier, F., Guigues, L., Deriche, R.,
A framework for constrained multi-scale range image segmentation,
ICIP03(II: 443-446).
IEEE DOI 0312
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Parker, B.,
Range estimation via multi-dimensional segmentation,
ICIP03(I: 993-996).
IEEE DOI 0312
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Priese, L.[Lutz], Sturm, P.[Patrick], Wang, H.J.[Hao-Jun],
Hierarchical Cell Structures for Segmentation of Voxel Images,
SCIA05(6-16).
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Sturm, P.[Patrick], Priese, L.[Lutz],
3D-Color-Structure-Code: A Hierarchical Region Growing Method for Segmentation of 3D-Images,
SCIA03(603-608).
Springer DOI 0310
BibRef
Earlier:
Properties of a Three-Dimensional Island Hierarchy for Segmentation of 3D Images with the Color Structure Code,
DAGM02(274 ff.).
Springer DOI 0303
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Deighton, M.[Matthew], Petrou, M.[Maria],
Supervised Segmentation of Volume Textures Using 3D Probabilistic Relaxation,
SCIA03(869-876).
Springer DOI 0310
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Sappa, A.D.,
Improving segmentation results by studying surface continuity,
ICPR02(II: 929-932).
IEEE DOI 0211
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Cinque, L.[Luigi], Corzani, F., Levialdi, S., Cucchiara, R.,
Improvement in range segmentation parameters tuning,
ICPR02(I: 176-179).
IEEE DOI 0211
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Robles-Kelly, A.[Antonio], Sarkar, S., Hancock, E.R.[Edwin R.],
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ICPR02(II: 639-642).
IEEE DOI 0211
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Robles-Kelly, A.[Antonio], Hancock, E.R.[Edwin R.],
A graph-spectral approach to surface segmentation,
ICPR02(III: 509-512).
IEEE DOI 0211
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And:
A graph-spectral approach to correspondence matching,
ICPR02(IV: 176-179).
IEEE DOI 0211

See also Graph-Spectral Approach to Shape-From-Shading, A.
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Saupe, D., Kuska, J.P.,
Compression of isosurfaces for structured volumes with context modelling,
3DPVT02(384-390).
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Earlier:
Compression of Isosurfaces for Structured Volumes,
VMV01(xx-yy).
PDF File. 0209
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Saupe, D., Toelke, J.,
Optimal Memory Constrained Isosurface Extraction,
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Borovikov, E., Davis, L.S.,
3D shape estimation based on density driven model fitting,
3DPVT02(116-125).
IEEE DOI 0206
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Boada, I., Navazo, I.,
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Bock, M.E., Guerra, C.,
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VMV01(xx-yy).
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Earlier:
A geometric approach to the segmentation of range images,
3DIM99(261-269).
IEEE DOI 9910
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Fernández, J.[Josep], Aranda, J.[Joan],
Image Segmentation Combining Region Depth and Object Features,
ICPR00(Vol I: 618-621).
IEEE DOI 0009
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Cinque, L.[Lugi], Cucchiara, R.[Rita], Levialdi, S.[Stefano], Martinz, S.[Stefano], Pignalberi, G.[Gianluca],
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IEEE DOI 0009
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Goldschneider, J.,
Variational Segmentation by Piecewise Facet Models with Application to Range Imagery,
ICIP00(Vol I: 812-815).
IEEE DOI 0008
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Torr, P.H.S., Dick, A.R., Cipolla, R.,
Layer Extraction with a Bayesian Model of Shapes,
ECCV00(II: 273-289).
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Skrinjar, O.[Oskar], Tagare, H.[Hemant], Duncan, J.S.[James S.],
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Haindl, M.[Michal], Zid, P.[Pavel],
Multimodal Range Image Segmentation by Curve Grouping,
ICPR06(IV: 9-12).
IEEE DOI 0609
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Haindl, M.[Michal], Havlícek, V.[Vojtech], Zid, P.[Pavel],
Automatic Acquisition of Planar-faced Virtual Models,
ICPR00(Vol I: 987-990).
IEEE DOI 0009
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Žid, P.[Pavel], Haindl, M.[Michal],
Fast Segmentation of Planar Surfaces in Range Images,
ICPR98(Vol II: 985-987).
IEEE DOI 9808
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Earlier:
Fast segmentation of range images,
CIAP97(I: 295-302).
Springer DOI 9709
BibRef

Jiang, X.Y.[Xiao-Yi], Kuhni, P.[Peter],
Search-Based Contour Closure in Range Images,
ICPR98(Vol I: 16-18).
IEEE DOI 9808
BibRef

Koenderink, J.J.[Jan J.], van Doorn, A.J.[Andrea J.],
Shape from Chebyshev nets,
ECCV98(II: 215).
Springer DOI BibRef 9800
Earlier:
Local Features of Smooth Shapes: Ridges and Courses,
SPIE(2031), 1993, pp. 2-13. BibRef

Powell, M.W.[Mark W.], Bowyer, K.W.[Kevin W.], Jiang, X.Y.[Xiao-Yi], Bunke, H.[Horst],
Comparing Curved-Surface Range Image Segmenters,
ICCV98(286-291).
IEEE DOI BibRef 9800

de Piero, F.W., Trivedi, M.M.,
Real-Time Range Image Segmentation Using Adaptive Kernels and Kalman Filtering,
ICPR96(III: 573-577).
IEEE DOI 9608
(Univ. of Tennessee, USA) BibRef

Zhao, C., Zhao, D., Chen, Y.,
Simplified Gaussian and Mean Curvatures to Range Image Segmentation,
ICPR96(II: 427-431).
IEEE DOI 9608
(Univ. of Michigan, USA) BibRef

Chiavetta, F.[Franco], di Gesù, V.[Vito],
An unsupervised region growing method for 3D image segmentation,
CAIP95(49-56).
Springer DOI 9509
BibRef

Schillo, C., Herrmann, G., Ackermann, F., Posch, S., Sagerer, G.,
Statistical classification and segmentation of biomolecular surfaces,
ICIP95(III: 560-563).
IEEE DOI 9510
BibRef

Gregoriou, G.K., Waks, A., Tretiak, O.J.,
Adaptive segmentation of images of objects with smooth surfaces,
CVPR93(772-773).
IEEE DOI 0403
BibRef

Hsu, S., Mundy, J.L.,
Regionalization of Image Data Using Surface Approximation,
PRIP79(314-317). BibRef 7900

Hsu, S., Mundy, J.L., Beaudet, P.R.,
Web Representation of Image Data,
ICPR78(765-769). BibRef 7800

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Depth Object Segmentation, Point Cloud Segmentation .