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 Abstract. IEEE Top Reference.
WWW Version. 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 Top Reference. 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.,
A Methodology for Evaluating Range Image Segmentation Techniques,
WACV94(264-271).
IEEE Abstract. IEEE Top Reference. 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 Reference
HTML Version. 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,
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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 Reference 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 Reference 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 Abstract. IEEE Top Reference.
WWW Version. 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 Abstract. IEEE Top Reference. 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.
WWW Version. BibRef 9401
Earlier:
Volumetric description of solids of revolution in a range image,
ICPR90(I: 303-308).
IEEE DOI Reference 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 Abstract. IEEE Top Reference.
WWW Version. BibRef 8906
Earlier:
A Hybrid Approach to Range Image Segmentation,
ICPR88(I: 1-5).
IEEE DOI Reference 8811Generate 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.
WWW Version. BibRef 9105
Earlier:
A Parallel Technique for Three-Dimensional Image Segmentation,
ICPR90(I: 201-203).
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Thonnat, M.,
Semantic Interpretation of 3-D Stereo Data: Finding the Main Structures,
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Earlier: ICPR86(1051-1054). BibRef

Ma, R., Thonnat, M.,
Object Detection in Outdoor Scenes by Disparity Map Segmentation,
ICPR92(I:546-549).
IEEE DOI Reference BibRef 9200

Han, J.H., and Volz, R.A.,
Region Grouping from a Range Image,
CVPR88(241-248).
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Abdelmalek, N.N.,
Algebraic Error Analysis for Surface Curvatures and Segmentation of 3-D Range Images,
PR(23), No. 8, 1990, pp. 807-817.
WWW Version. BibRef 9000
Earlier:
Algebraic error analysis for surface curvatures of 3-D range images obtained by different methods,
ICPR90(I: 529-534).
IEEE DOI Reference 9006 BibRef

Bhandarkar, S.M., Siebert, A.,
Integrating Edge and Surface Information for Range Image Segmentation,
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WWW Version. BibRef 9209

Parvin, B., and Medioni, G.G.[Gerard G.],
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B-reps from Unregistered Multiple Range Image,
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Earlier:
Segmentation of Range Images into Planar Surfaces by Split and Merge,
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Strasters, K.C., and Gerbrands, J.J.,
Three-Dimensional Image Segmentation Using a Split, Merge and Group Approach,
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Strasters, K.C., Smeulders, A.W.M., vander Voort, H.T.M.,
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Hoover, A., Goldgof, D., Bowyer, K.W.,
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Hoover, A., Goldgof, D., Bowyer, K.W.,
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Bose, S.K., Biswas, K.K., Gupta, S.K.,
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Chatterji, G.B., Sridhar, B.,
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IEEE Top Reference. 9611 BibRef

Baccar, M., Gee, L.A., Gonzalez, R.C., Abidi, M.A.,
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PR(29), No. 10, October 1996, pp. 1673-1687.
WWW Version. Data Fusion. BibRef 9610

Umasuthan, M., Wallace, A.M.,
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Wu, M.C., Liu, C.R.,
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Rimey, R.D., Cohen, F.S.,
A Maximum-Likelihood Approach to Segmenting Range Data,
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Zhao, D.M., Zhang, X.T.,
Range-Data-Based Object Surface Segmentation via Edges and Critical-Points,
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IEEE DOI Reference 9705 BibRef

Chen, Y.H., Liu, C.Y.,
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Baccar, M., Gee, L.A., Abidi, M.A.,
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JMIV(11), No. 3, December 1999, pp. 195-205.
WWW Version. 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 Abstract. IEEE Top Reference.
WWW Version. 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,
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Benlamri, R.[Rachid], Al-Marzooqi, Y.[Yousuf],
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WWW Version. 0407 BibRef

Werghi, N., Fisher, R.B., Robertson, C., Ashbrook, A.P.,
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Robertson, C.[Craig], Fisher, R.B.[Robert B.],
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Ashbrook, A.P., Fisher, R.B., Robertson, C., Werghi, N.,
Construction of Articulated Models from Range Data,
BMVC99(183-192),
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Earlier:
Segmentation of Range Data into Rigid Subsets Using Surface Patches,
ICCV98(201-206).
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BMVC97(530-539). BibRef Edinburghrange data segmentation
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Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
The Facet Model for Descriptions .