Keith Price Bibliography Snakes, Region Segmentation Issues

8.7.1.2 Snakes, Region Segmentation Issues

Chapter Contents (Back)
Deformable Curves. Snakes. Active Contours. Segmentation.

Guichard, F.[Frederic], and Dal Maso, G., Morel, J.M.[Jean-Michel], and Solimini, S.,
A variational method in image segmentation: Existence and approximation results,
ActaMat(168), 1992, pp. 89-151. BibRef 9200

Sinclair, D.A., Blake, A., Smith, S., and Rothwell, C.A.,
Planar Region Detection and Motion Recovery,
IVC(11), No. 4, May 1993, pp. 229-234.
WWW Version. BibRef 9305
Earlier: BMVC92(xx-yy).
PDF Version. 9209
BibRef

Sinclair, D., Blake, A.,
Isoperimetric Normalization of Planar Curves,
PAMI(16), No. 8, August 1994, pp. 769-777.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9408

Sinclair, D., Blake, A.,
Quantitative Planar Region Detection,
IJCV(18), No. 1, April 1996, pp. 77-91.
Springer DOI Link 9605
BibRef

Ronfard, R.,
Region-Based Strategies for Active Contour Models,
IJCV(13), No. 2, October 1994, pp. 229-251.
Springer DOI Link Introduces heuristic rules to derive equations for a snake, using local statistics of the regions around the contour. BibRef 9410

Ivins, J.P.[Jim P.], Porrill, J.[John],
Active-Region Models for Segmenting Textures and Colors,
IVC(13), No. 5, June 1995, pp. 431-438.
WWW Version. BibRef 9506
And:
Active-Region Models for Segmenting Medical Images,
ICIP94(II: 227-231).
IEEE DOI Link 9411
BibRef
Earlier:
Statistical Snakes: Active Region Models,
BMVC94(xx-yy).
PDF Version. 9409
BibRef
And: A1, Only: Ph.D.Thesis, Univ. of Sheffield, 1996. BibRef

Ivins, J.P.[Jim P.], Porrill, J.[John],
Constrained Active Region Models for Fast Tracking in Color Image Sequences,
CVIU(72), No. 1, October 1998, pp. 54-71.
WWW Version. BibRef 9810

Zhu, S.C., Yuille, A.,
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation,
PAMI(18), No. 9, September 1996, pp. 884-900.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9609
Earlier: Add A2: Lee, T.S., ICCV95(416-423).
IEEE DOI Link
WWW Version. BibRef
And:
Region Competition and its Analysis: A Unified Theory for Image Segmentation,
HarvardTR-95-07, 1995. Bayes Nets. Region Growing. Minimum Description Length. Color Models. These are the same if viewed in the right way. Problems with different size regions. BibRef

Tu, Z.W.[Zhuo-Wen], Chen, X.R.[Xiang-Rong], Yuille, A.L.[Alan L.], Zhu, S.C.[Song-Chun],
Image Parsing: Unifying Segmentation, Detection, and Recognition,
IJCV(63), No. 2, July 2005, pp. 113-140.
Springer DOI Link 0501
BibRef
And: CLOR06(545-576).
Springer DOI Link 0711
BibRef
Earlier: ICCV03(18-25).
IEEE DOI Link 0311
Award, Marr Prize. BibRef

Dubinskiy, A., Zhu, S.C.[Song Chun],
A multi-scale generative model for animate shapes and parts,
ICCV03(249-256).
IEEE DOI Link 0311
Model shapes and parts. BibRef

Chan, F.H.Y., Lam, F.K., Poon, P.W.F., Zhu, H., Chan, K.H.,
Object Boundary Location by Region and Contour Deformation,
VISP(143), No. 6, December 1996, pp. 353-360. 9702
BibRef

Milroy, M.J., Bradley, C., Vickers, G.W.,
Segmentation of a Wrap-Around Model Using an Active Contour,
CAD(29), No. 4, April 1997, pp. 299-320. 9703
BibRef

Grzeszczuk, R.P.[Robert P.], Levin, D.N.[David N.],
Brownian Strings: Segmenting Images with Stochastically Deformable Contours,
PAMI(19), No. 10, October 1997, pp. 1100-1114.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9710
Use simulated annealing so less dependant on initial contour. BibRef

Ip, H.H.S., Shen, D.G.,
An Affine-Invariant Active Contour Model (AI-Snake) for Model-Based Segmentation,
IVC(16), No. 2, February 20 1998, pp. 135-146.
WWW Version. 9803
BibRef

Hewer, G.A., Kenney, C., Manjunath, B.S.,
Variational Image Segmentation Using Boundary Functions,
IP(7), No. 9, September 1998, pp. 1269-1282.
IEEE DOI Link 9809

PDF Version. BibRef
Earlier:
Image Segmentation via Functionals Based on Boundary Functions,
ICIP96(I: 813-816).
IEEE DOI Link
PDF Version. BibRef

Vilarino, D.L., Brea, V.M., Cabello, D., Pardo, J.M.,
Discrete-Time CNN for Image Segmentation by Active Contours,
PRL(19), No. 8, June 1998, pp. 721-734. 9808
BibRef

Pardo, X.M., Cabello, D.,
Biomedical active segmentation guided by edge saliency,
PRL(21), No. 6-7, June 2000, pp. 559-572. 0006
BibRef

Vilariño, D.L.[David L.], Cabello, D.[Diego], Pardo, X.M.[Xose M.], Brea, V.M.[Victof M.],
Cellular neural networks and active contours: A tool for image segmentation,
IVC(21), No. 2, February 2003, pp. 189-204.
WWW Version. 0301
BibRef
Earlier:
Pixel-level Snakes,
ICPR00(Vol I: 640-643).
IEEE DOI Link
HTML Version. 0009
BibRef

Ngoi, K.P., Jia, J.C.,
An active contour model for colour region extraction in natural scenes,
IVC(17), No. 13, 1 November 1999, pp. 955-966.
WWW Version. 9911
BibRef
Earlier:
A Robust Active Contour Model for Natural Scene Contour Extraction with Automatic Thresholding,
ECCV96(II:335-346).
Springer DOI Link Extract various objects from images. BibRef

Chesnaud, C.[Christophe], Réfrégier, P.[Philippe], Boulet, V.[Vlady],
Statistical Region Snake-Based Segmentation Adapted to Different Physical Noise Models,
PAMI(21), No. 11, November 1999, pp. 1145-1157.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9912
Region snakes, not edge snakes, base on statistics of the region inside and outside the snake. The examples seem to show extraction with very low contrasts. BibRef

Sclaroff, S.[Stan], Liu, L.F.[Li-Feng],
Deformable Shape Detection and Description via Model-Based Region Grouping,
PAMI(23), No. 5, May 2001, pp. 475-489.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0105
BibRef
And: Corrections: PAMI(23), No. 6, June 2001, pp. 686.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0106
BibRef
Earlier: A2, A1: CVPR99(II: 21-27).
IEEE Abstract. IEEE Top Reference.
WWW Version. Partition the image using deformable shape templates. By using learned templates, shapes are segmented from background. BibRef

Liu, L.F.[Li-Feng], Sclaroff, S.[Stan],
Deformable model-guided region split and merge of image regions,
IVC(22), No. 4, 1 April 2004, pp. 343-354.
WWW Version. 0402
BibRef
Earlier:
Region Segmentation via Deformable Model-Guided Split and Merge,
ICCV01(I: 98-104).
IEEE DOI Link 0106
BibRef
And:
Shape-Guided Split and Merge of Image Regions,
VF01(367 ff.).
HTML Version. 0209
BibRef

Tsai, A.[Andy], Yezzi, Jr., A.J.[Anthony J.], Willsky, A.S.[Alan S.],
Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification,
IP(10), No. 8, August 2001, pp. 1169-1186.
IEEE DOI Link 0108
BibRef

Yezzi, Jr., A.J.[Anthony J.], Tsai, A.[Andy], Willsky, A.S.[Alan S.],
A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations,
JVCIR(13), No. 1/2, March/June 2002, pp. 195-216.
WWW Version. 0204
BibRef
Earlier: A2, A1, A3:
A Curve Evolution Approach to Smoothing and Segmentation Using the Mumford-Shah Functional,
CVPR00(I: 119-124).
IEEE Abstract. IEEE Top Reference.
WWW Version. 0005
BibRef
Earlier:
Binary and ternary flows for image segmentation,
ICIP99(II:1-5).
IEEE Abstract. IEEE Top Reference. BibRef
And:
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery,
ICCV99(898-903).
IEEE DOI Link See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Tsai, A.[Andy], Yezzi, Jr., A.J.[Anthony J.], Wells, III, W.M.[William M.], Tempany, C.[Clare], Tucker, D.[Dewey], Fan, A.[Ayres], Grimson, W.E.L.[W. Eric L.], Willsky, A.S.[Alan S.],
Model-Based Curve Evolution Technique for Image Segmentation,
CVPR01(I:463-468).
IEEE Abstract. IEEE Top Reference. 0110
Award, CVPR, Student HM. For known objects. BibRef

Kim, J.[Junno], Tsai, A., Cetin, M., Willsky, A.S.,
A curve evolution-based variational approach to simultaneous image restoration and segmentation,
ICIP02(I: 109-112).
IEEE Abstract. IEEE Top Reference. 0210
BibRef

Tsai, A.,
Curve Evolution, Boundary-value Stochastic Processes, the Mumford-Shah Problem, and Missing Data Applications,
ICIP00(Vol III: 588-591).
IEEE Abstract. IEEE Top Reference. 0008
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Unal, G., Krim, H., Yezzi, A.J.,
Stochastic differential equations and geometric flows,
IP(11), No. 12, December 2002, pp. 1405-1416.
IEEE DOI Link 0301
Local stochastic interpretation of the basic curve smoothing equation, the geometric heat equation, this evolution amounts to a tangential diffusion movement of the particles along the contour. BibRef

Unal, G.[Gozde], Yezzi, A.J.[Anthony J.], Krim, H.[Hamid],
Information-Theoretic Active Polygons for Unsupervised Texture Segmentation,
IJCV(62), No. 3, May 2005, pp. 199-220.
Springer DOI Link 0501
BibRef

Unal, G.[Gozde], Krim, H.[Hamid], Yezzi, A.J.[Anthony J.],
Fast Incorporation of Optical Flow Into Active Polygons,
IP(14), No. 6, June 2005, pp. 745-759.
IEEE DOI Link 0505
BibRef
Earlier:
Active polygon for object tracking,
3DPVT02(696-699). 0206
BibRef

Unal, G., Krim, H.,
Feature-preserving Flows: A Stochastic Differential Equation's View,
ICIP00(Vol I: 896-899).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Unal, G., Nain, D., Ben-Arous, G., Shimk-In, N., Tannenbaum, A., Zeitouni, O.,
Algorithms for stochastic approximations of curvature flows,
ICIP03(II: 651-654).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Germain, O.[Olivier], Réfrégier, P.[Philippe],
Statistical active grid for segmentation refinement,
PRL(22), No. 10, August 2001, pp. 1125-1132.
HTML Version. 0108
BibRef

Jang, J.H.[Jeong-Hun], Hong, K.S.[Ki-Sang],
Detection of curvilinear structures and reconstruction of their regions in gray-scale images,
PR(35), No. 4, April 2002, pp. 807-824.
WWW Version. 0201
See also Linear band detection based on the Euclidean distance transform and a new line segment extraction method. BibRef

Ji, L.[Lilian], Yan, H.[Hong],
Robust Topology-adaptive Snakes for Image Segmentation,
IVC(20), No. 2, February 2002, pp. 147-164.
WWW Version. 0202
BibRef
Earlier: ICIP01(II: 797-800).
IEEE Abstract. IEEE Top Reference. 0108
BibRef

Ji, L.[Lilian], Yan, H.[Hong],
Attractable snakes based on the greedy algorithm for contour extraction,
PR(35), No. 4, April 2002, pp. 791-806.
WWW Version. 0201
BibRef

Ji, L.[Lilian], Yan, H.[Hong],
Loop-free snakes for highly irregular object shapes,
PRL(23), No. 5, March 2002, pp. 579-591.
HTML Version. 0202
BibRef
Earlier:
Loop-Free Snakes for Image Segmentation,
ICIP99(III:193-197).
IEEE Abstract. IEEE Top Reference. BibRef

Jehan-Besson, S.[Stéphanie], Barlaud, M.[Michel], Aubert, G.[Gilles],
A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection,
JASP(2002), No. 6, June 2002, pp. 572-581. 0208
BibRef
Earlier:
Video Objects Segmentation Using Eulerian Region-Based Active Contours,
ICCV01(I: 353-360).
IEEE DOI Link 0106
BibRef
And:
Region-based Active Contours for Video Object Segmentation with Camera Compensation,
ICIP01(II: 61-64).
IEEE Abstract. IEEE Top Reference. 0108
BibRef
Earlier:
Detection and Tracking of Moving Objects Using a New Level Set Based Method,
ICPR00(Vol III: 1100-1105).
IEEE DOI Link 0009
BibRef

Herbulot, A.[Ariane], Jehan-Besson, S.[Stéphanie], Duffner, S.[Stefan], Barlaud, M.[Michel], Aubert, G.[Gilles],
Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures,
JMIV(25), No. 3, October 2006, pp. 365-386.
Springer DOI Link 0611
BibRef
Earlier: A1, A2, A4, A5, Only:
Shape gradient for multi-modal image segmentation using mutual information,
ICIP04(IV: 2729-2732).
IEEE DOI Link 0505
See also DREAM 2 S: Deformable Regions Driven by an Eulerian Accurate Minimization Method for Image and Video Segmentation. BibRef

Lecellier, F.[Francois], Jehan-Besson, S.[Stephanie], Fadili, J.[Jalal], Aubert, G.[Gilles], Revenu, M.[Marinette],
Optimization of Divergences within the Exponential Family for Image Segmentation,
SSVM09(137-149).
Springer DOI Link 0906
BibRef
Earlier: A1, A3, A2, A5, A4:
Region-based active contours and sparse representations for texture segmentation,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Jehan-Besson, S.[Stephanie], Barlaud, M.[Michel], Aubert, G.[Gilles], Faugeras, O.D.,
Shape gradients for histogram segmentation using active contours,
ICCV03(408-415).
IEEE DOI Link 0311
BibRef

Castaud, M., Barlaud, M.,
Video segmentation using active contours on a group of pictures,
ICIP02(II: 81-84).
IEEE Abstract. IEEE Top Reference. 0210
BibRef

Lecellier, F., Jehan-Besson, S., Fadili, J., Aubert, G., Revenu, M., Saloux, E.,
Region-Based Active Contour with Noise and Shape Priors,
ICIP06(1649-1652). 0610

IEEE DOI Link BibRef

Gastaud, M., Barlaud, M., Aubert, G.,
Combining shape prior and statistical features for active contour segmentation,
CirSysVideo(14), No. 5, May 2004, pp. 726-734.
IEEE Abstract. IEEE Top Reference. 0407
BibRef
Earlier:
Tracking video objects using active contours,
Motion02(90-95).
IEEE Abstract. IEEE Top Reference. 0303
BibRef

Debreuve, É., Gastaud, M., Barlaud, M., Aubert, G.,
Using the Shape Gradient for Active Contour Segmentation: from the Continuous to the Discrete Formulation,
JMIV(28), No. 1, May 2007, pp. 47-66.
Springer DOI Link 0710
See also Outer-Layer Based Tracking using Entropy as a Similarity Measure. See also DREAM 2 S: Deformable Regions Driven by an Eulerian Accurate Minimization Method for Image and Video Segmentation. BibRef

Boltz, S.[Sylvain], Debreuve, É.[Éric], Barlaud, M.[Michel],
Joint Appearance and Deformable Shape for Nonparametric Segmentation,
HUMO07(180-195).
Springer DOI Link 0710
BibRef
And:
A High Dimensional Framework for Joint Color-Spatial Segmentation,
ICIP07(VI: 313-316).
IEEE DOI Link 0709
See also Motion and Appearance Nonparametric Joint Entropy for Video Segmentation. BibRef

Debreuve, E., Barlaud, M., Marmorat, J.P., Aubert, G.,
Active Contour Segmentation with a Parametric Shape Prior: Link with the Shape Gradient,
ICIP06(1653-1656). 0610

IEEE DOI Link BibRef

Jehan-Besson, S., Gastaud, M., Barlaud, M., Aubert, G.,
Region-based active contours using geometrical and statistical features for image segmentation,
ICIP03(II: 643-646).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Mahamud, S.[Shyjan], Williams, L.R.[Lance R.], Thornber, K.K.[Karvel K.], Xu, K.L.[Kang-Lin],
Segmentation of multiple salient closed contours from real images,
PAMI(25), No. 4, April 2003, pp. 433-444.
IEEE Abstract. IEEE Top Reference. 0304
Based on a global property, identify smooth closed contours. BibRef

Mahamud, S., Thornber, K.K., Williams, L.R.,
Segmentation of Salient Closed Contours from Real Images,
ICCV99(891-897).
IEEE DOI Link BibRef 9900

Cremers, D.[Daniel], Tischhäuser, F.[Florian], Weickert, J.[Joachim], Schnörr, C.[Christoph],
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional,
IJCV(50), No. 3, December 2002, pp. 295-313.
WWW Version.
PDF Version. 0211
BibRef

Cremers, D.[Daniel], Kohlberger, T.[Timo], Schnörr, C.[Christoph],
Shape statistics in kernel space for variational image segmentation,
PR(36), No. 9, September 2003, pp. 1929-1943.
WWW Version. 0307
BibRef
Earlier:
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation,
ECCV02(II: 93 ff.).
HTML Version. 0205

Postscript Version. BibRef
And:
Nonlinear Shape Statistics via Kernel Spaces,
DAGM01(269-276). BibRef
And:
Diffusion-Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework,
LevelSet01(137-144).
Postscript Version. 0106
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Cremers, D.[Daniel],
Statistical Shape Knowledge in Variational Image Segmentation,
Ph.D.Thesis, Department of Mathematics and Computer Science, University of Mannheim, Germany, July 2002.
PDF Version. BibRef 0207

Cremers, D.[Daniel], Schmidt, F.R.[Frank R.], Barthel, F.[Frank],
Shape priors in variational image segmentation: Convexity, Lipschitz continuity and globally optimal solutions,
CVPR08(1-6).
IEEE DOI Link 0806
BibRef

Schoenemann, T.[Thomas], Cremers, D.[Daniel],
Globally optimal shape-based tracking in real-time,
CVPR08(1-6).
IEEE DOI Link 0806
BibRef

Schoenemann, T.[Thomas], Cremers, D.[Daniel],
Matching non-rigidly deformable shapes across images: A globally optimal solution,
CVPR08(1-6).
IEEE DOI Link 0806
BibRef

Schoenemann, T.[Thomas], Schmidt, F.R., Cremers, D.[Daniel],
Image Segmentation with Elastic Shape Priors via Global Geodesics in Product Spaces,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Schmidt, F.R.[Frank R.], Cremers, D.[Daniel],
A Closed-Form Solution for Image Sequence Segmentation with Dynamical Shape Priors,
DAGM09(31-40).
Springer DOI Link 0909
BibRef

Schoenemann, T.[Thomas], Cremers, D.[Daniel],
Globally Optimal Image Segmentation with an Elastic Shape Prior,
ICCV07(1-6).
IEEE DOI Link 0710
BibRef

Schoenemann, T.[Thomas], Cremers, D.[Daniel],
Introducing Curvature into Globally Optimal Image Segmentation: Minimum Ratio Cycles on Product Graphs,
ICCV07(1-6).
IEEE DOI Link 0710
BibRef

Lellmann, J.[Jan], Kappes, J.H.[Jörg H.], Yuan, J.[Jing], Becker, F.[Florian], Schnörr, C.[Christoph],
Convex Multi-class Image Labeling by Simplex-Constrained Total Variation,
SSVM09(150-162).
Springer DOI Link 0906
BibRef

Kappes, J.H.[Jörg H.], Schnörr, C.[Christoph],
MAP-Inference for Highly-Connected Graphs with DC-Programming,
DAGM08(xx-yy).
Springer DOI Link 0806
BibRef

Bergtholdt, M.[Martin], Kappes, J.H.[Jörg H.], Schnörr, C.[Christoph],
Learning of Graphical Models and Efficient Inference for Object Class Recognition,
DAGM06(273-283).
Springer DOI Link 0610
BibRef

Bergtholdt, M.[Martin], Schnörr, C.[Christoph],
Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes,
DAGM05(342).
Springer DOI Link 0509
BibRef

Cremers, D.[Daniel], Schnörr, C.[Christoph],
Statistical shape knowledge in variational motion segmentation,
IVC(21), No. 1, January 2003, pp. 77-86.
WWW Version.
PDF Version. 0301
BibRef

Cremers, D.[Daniel], Sochen, N.A.[Nir A.], Schnörr, C.[Christoph],
A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation,
IJCV(66), No. 1, January 2006, pp. 67-81.
Springer DOI Link 0601
BibRef
Earlier:
Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling,
ScaleSpace03(388-400).
HTML Version. 0310
BibRef

Cremers, D.,
A variational framework for image segmentation combining motion estimation and shape regularization,
CVPR03(I: 53-58).
IEEE Abstract. IEEE Top Reference. 0307
BibRef

Manay, S.[Siddharth], Cremers, D.[Daniel], Hong, B.W.[Byung-Woo], Yezzi, A.J.[Anthony J.], Soatto, S.[Stefano],
Integral Invariants for Shape Matching,
PAMI(28), No. 10, October 2006, pp. 1602-1618.
IEEE DOI Link 0609
Integral invariants as opposed to differential invariants. BibRef

Manay, S.[Siddharth], Cremers, D.[Daniel], Yezzi, A.J.[Anthony J.], Soatto, S.[Stefano],
One-Shot Integral Invariant Shape Priors for Variational Segmentation,
EMMCVPR05(414-426).
Springer DOI Link 0601
BibRef

Jackson, J.D.[Jeremy D.], Yezzi, A.J.[Anthony J.], Soatto, S.[Stefano],
Dynamic Shape and Appearance Modeling via Moving and Deforming Layers,
IJCV(79), No. 1, August 2008, pp. xx-yy.
Springer DOI Link 0804
BibRef
Earlier: EMMCVPR05(427-438).
Springer DOI Link 0601
BibRef
And:
Joint Priors for Variational Shape and Appearance Modeling,
MultiView07(1-7).
IEEE DOI Link 0706
BibRef

Hintermüller, M.[Michael], Ring, W.[Wolfgang],
An Inexact Newton-CG-Type Active Contour Approach for the Minimization of the Mumford-Shah Functional,
JMIV(20), No. 1-2, January-March 2004, pp. 19-42.
WWW Version. 0403
BibRef

Dong, Y.Q.[Yi-Qiu], Hintermüller, M.[Michael],
Multi-scale Total Variation with Automated Regularization Parameter Selection for Color Image Restoration,
SSVM09(271-281).
Springer DOI Link 0906
BibRef

Hintermüller, M., Laurain, A.,
Multiphase Image Segmentation and Modulation Recovery Based on Shape and Topological Sensitivity,
JMIV(35), No. 1, September 2009, pp. xx-yy.
Springer DOI Link 0907
BibRef

Xie, X.H.[Xiang-Hua], Mirmehdi, M.[Majid],
RAGS: Region-Aided Geometric Snake,
IP(13), No. 5, May 2004, pp. 640-652.
IEEE DOI Link 0404
BibRef
Earlier:
Geodesic Colour Active Contour Resistent to Weak Edges and Noise,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Xie, X.H.[Xiang-Hua], Mirmehdi, M.[Majid],
Implicit Active Model using Radial Basis Function Interpolated Level Sets,
BMVC07(xx-yy).
PDF Version. 0709
BibRef

Xie, X.H.[Xiang-Hua], Mirmehdi, M.[Majid],
MAC: Magnetostatic Active Contour Model,
PAMI(30), No. 4, April 2008, pp. 632-646.
WWW Version. 0803
BibRef
And: Correction: PAMI(30), No. 5, May 2008, pp. xx.
IEEE DOI Link 0803
BibRef
Earlier:
Magnetostatic Field for the Active Contour Model: A Study in Convergence,
BMVC06(I:127).
PDF Version. 0609
BibRef

Yang, R.H.[Rong-Hua], Mirmehdi, M.[Majid], Xie, X.H.[Xiang-Hua],
A Charged Active Contour Based on Electrostatics,
ACIVS06(173-184).
Springer DOI Link 0609
BibRef

Yang, R.H.[Rong-Hua], Mirmehdi, M.[Majid],
A Charged Geometric Model for Active Contours,
ICPR06(II: 183-186).
WWW Version. 0609
BibRef

Hanek, R.[Robert], Beetz, M.[Michael],
The Contracting Curve Density Algorithm: Fitting Parametric Curve Models to Images Using Local Self-Adapting Separation Criteria,
IJCV(59), No. 3, September-October 2004, pp. 233-258.
WWW Version. 0405
Locally adaptive criteria in fitting. BibRef

Hanek, R.[Robert],
The Contracting Curve Density Algorithm and its Application to Model-based Image Segmentation,
CVPR01(I:797-804).
IEEE Abstract. IEEE Top Reference. 0110
BibRef

Agnus, V.[Vincent],
Segmentation d'images par cooperation contours-regions,
M.S.Thesis, 1997, Strasbourg, France. Study an approach based on combining edge and regions techniques.
Postscript Version. BibRef 9700

Li, C.M.[Chun-Ming], Liu, J.D.[Jun-Dong], Fox, M.D.[Martin D.],
Segmentation of external force field for automatic initialization and splitting of snakes,
PR(38), No. 11, November 2005, pp. 1947-1960.
WWW Version. 0509
BibRef
Earlier:
Segmentation of Edge Preserving Gradient Vector Flow: An Approach Toward Automatically Initializing and Splitting of Snakes,
CVPR05(I: 162-167).
IEEE DOI Link 0507
See also Level Set Evolution without Re-Initialization: A New Variational Formulation. BibRef

Kim, J.[Junmo], Fisher, III, J.W., Yezzi, A.J., Cetin, M., Willsky, A.S.,
A nonparametric statistical method for image segmentation using information theory and curve evolution,
IP(14), No. 10, October 2005, pp. 1486-1502.
IEEE DOI Link 0510
BibRef
Earlier:
Nonparametric methods for image segmentation using information theory and curve evolution,
ICIP02(III: 797-800).
IEEE Abstract. IEEE Top Reference. 0210
BibRef
And: A1, A2, A4, A3, A5:
Incorporating complex statistical information in active contour-based image segmentation,
ICIP03(II: 655-658).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Kim, J.[Junmo], Çetin, M.[Müjdat], Willsky, A.S.[Alan S.],
Nonparametric shape priors for active contour-based image segmentation,
SP(87), No. 12, December, 2007, pp. 3021-3044.
Elsevier DOI Link 0905
BibRef

Vanzella, W., Torre, V.,
A Versatile Segmentation Procedure,
SMC-B(36), No. 2, April 2006, pp. 366-378.
IEEE DOI Link 0604
Regularize with Mumford-Shah ( See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. ) BibRef

Tao, T.C.Y.[Trevor Chi-Yuen], Crisp, D.J.[David James], van der Hoek, J.[John],
Mathematical Analysis of An Extended Mumford-Shah Model for Image Segmentation,
JMIV(24), No. 3, May 2006, pp. 327-340.
Springer DOI Link 0605
BibRef

Feddern, C.[Christian], Weickert, J.[Joachim], Burgeth, B.[Bernhard], Welk, M.[Martin],
Curvature-Driven PDE Methods for Matrix-Valued Images,
IJCV(69), No. 1, August 2006, pp. 93-107.
Springer DOI Link 0606
BibRef
Earlier: A3, A4, A1, A2:
Morphological Operations on Matrix-Valued Images,
ECCV04(Vol IV: 155-167).
WWW Version. 0405
Applied to diffusion tensor magnetic resonance imaging. Detecting edges in tensor fields. Tensorial active contours. See also Tensor-driven Active Contour Model for Moving Object Segmentation, A. BibRef

Burgeth, B.[Bernhard], Bruhn, A.[Andres], Didas, S.[Stephan], Weickert, J.[Joachim], Welk, M.[Martin],
Morphology for matrix data: Ordering versus PDE-based approach,
IVC(25), No. 4, April 2007, pp. 496-511.
WWW Version. 0702
Mathematical morphology; Dilation; Erosion; Matrix-valued images; Diffusion tensor MRI; Loewner ordering; Nonlinear partial differential equation BibRef

Bresson, X.[Xavier], Vandergheynst, P.[Pierre], Thiran, J.P.[Jean-Philippe],
A Variational Model for Object Segmentation Using Boundary Information and Shape Prior Driven by the Mumford-Shah Functional,
IJCV(68), No. 2, June 2006, pp. 145-162.
Springer DOI Link 0606
BibRef
Earlier:
A priori information in image segmentation: energy functional based on shape statistical model and image information,
ICIP03(III: 425-428).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Bresson, X.[Xavier], Vandergheynst, P.[Pierre], Thiran, J.P.[Jean-Philippe],
Multiscale Active Contours,
IJCV(70), No. 3, December 2006, pp. 197-211.
Springer DOI Link 0608
BibRef
Earlier: ScaleSpace05(167-178).
WWW Version. 0505
BibRef

Bogdanova, I., Bresson, X.[Xavier], Thiran, J.P.[Jean-Philippe], Vandergheynst, P.[Pierre],
Scale Space Analysis and Active Contours for Omnidirectional Images,
IP(16), No. 7, July 2007, pp. 1888-1901.
IEEE DOI Link 0707
BibRef

Bresson, X.[Xavier], Esedoglu, S.[Selim], Vandergheynst, P.[Pierre], Thiran, J.P.[Jean-Philippe], Osher, S.J.[Stanley J.],
Fast Global Minimization of the Active Contour/Snake Model,
JMIV(28), No. 2, June 2007, pp. 151-167.
Springer DOI Link 0710
BibRef

Houhou, N.[Nawal], Thiran, J.P.[Jean-Philippe], Bresson, X.[Xavier],
Fast texture segmentation model based on the shape operator and active contour,
CVPR08(1-8).
IEEE DOI Link 0806
BibRef

Houhou, N.[Nawal], Lemkaddem, A.[Alia], Duay, V.[Valerie], Allal, A.[Abdelkarim], Thiran, J.P.[Jean-Philippe],
Shape prior based on statistical map for active contour segmentation,
ICIP08(2284-2287).
IEEE DOI Link 0810
BibRef

Duay, V., Houhou, N., Thiran, J.P.,
Atlas-Based Segmentation of Medical Images Locally Constrained by Level Sets,
ICIP05(II: 1286-1289).
IEEE DOI Link 0512
BibRef

Bresson, X.[Xavier], Chan, T.F.[Tony F.],
Active Contours Based on Chambolle's Mean Curvature Motion,
ICIP07(I: 33-36).
IEEE DOI Link 0709
BibRef

Zagorchev, L.[Lyubomir], Goshtasby, A.[Ardeshir], Satter, M.[Martin],
R-snakes,
IVC(25), No. 6, 1 June 2007, pp. 945-959.
WWW Version. 0704
Image segmentation; Energy minimizing contours; R-snakes BibRef

Li, B.[Bing], Acton, S.T.[Scott T.],
Active Contour External Force Using Vector Field Convolution for Image Segmentation,
IP(16), No. 8, August 2007, pp. 2096-2106.
IEEE DOI Link 0709
BibRef
Earlier:
Vector Field Convolution for Image Segmentation using Snakes,
ICIP06(1637-1640). 0610

IEEE DOI Link BibRef
Earlier:
Feature Weighted Active Contours for Image Segmentation,
Southwest06(188-192).
IEEE DOI Link 0603
BibRef

Song, Y.,
A Topdown Algorithm for Computation of Level Line Trees,
IP(16), No. 8, August 2007, pp. 2107-2116.
IEEE DOI Link 0709
BibRef

Destrempes, F.[Francois], Mignotte, M.[Max], Angers, J.F.[Jean-Francois],
Localization of Shapes Using Statistical Models and Stochastic Optimization,
PAMI(29), No. 9, September 2007, pp. 1603-1615.
IEEE DOI Link 0709
Color segmentation based on deformations. BibRef

Michailovich, O.V.[Oleg V.], Rathi, Y.[Yogesh], Tannenbaum, A.[Allen],
Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow,
IP(16), No. 11, November 2007, pp. 2787-2801.
IEEE DOI Link 0709
BibRef
Earlier: A2, A3, A1:
Segmenting Images on the Tensor Manifold,
CVPR07(1-8).
IEEE DOI Link 0706
See also high-resolution technique for ultrasound harmonic imaging using sparse representations in gabor frames, A. BibRef

Koo, H.I.[Hyung Il], Lee, S.H.[Sang Hwa], Cho, N.I.[Nam Ik],
Bayesian object extraction from uncalibrated image pairs,
SP:IC(22), No. 10, November 2007, pp. 866-876.
WWW Version. 0711
Segmentation; MRF models; SIFT; Homography BibRef

Koo, H.I.[Hyung Il], Cho, N.I.[Nam Ik],
Boosting image segmentation,
ICIP08(3192-3195).
IEEE DOI Link 0810
BibRef

Koo, H.I.[Hyung Il], Lee, S.H.[Sang Hwa], Cho, N.I.[Nam Ik], Kim, S.K.[Seong Keun], Lee, D.H.[Dong Hahk], Lee, S.H.[Sung-Hoon],
MAP-Based Object Extraction from Uncalibrated Image Pair,
ICIP06(2425-2428). 0610

IEEE DOI Link BibRef

Ferrari, V.[Vittorio], Fevrier, L., Jurie, F.[Frederic], Schmid, C.[Cordelia],
Groups of Adjacent Contour Segments for Object Detection,
PAMI(30), No. 1, January 2008, pp. 36-51.
IEEE DOI Link 0711
BibRef
Earlier: A1, A3, A4, Only:
Accurate Object Detection with Deformable Shape Models Learnt from Images,
CVPR07(1-8).
IEEE DOI Link 0706
Scale invariant features from chains of straight line segments. BibRef

Bergo, F.P.G.[Felipe P.G.], Falcão, A.X.[Alexandre X.], Miranda, P.A.V.[Paulo A.V.], Rocha, L.M.[Leonardo M.],
Automatic Image Segmentation by Tree Pruning,
JMIV(29), No. 2-3, November 2007, pp. 141-162.
Springer DOI Link 0712
BibRef

Miranda, P.A.V.[Paulo A.V.], Falcão, A.X.[Alexandre X.],
Links Between Image Segmentation Based on Optimum-Path Forest and Minimum Cut in Graph,
JMIV(35), No. 2, October 2009, pp. xx-yy.
Springer DOI Link 0907
BibRef

Falcão, A.X.[Alexandre X.], Miranda, P.A.V.[Paulo A.V.], Rocha, A.[Anderson],
A Linear-Time Approach for Image Segmentation Using Graph-Cut Measures,
ACIVS06(138-149).
Springer DOI Link 0609
BibRef

Le Guyader, C.[Carole], Vese, L.A.[Luminita A.],
Self-Repelling Snakes for Topology-Preserving Segmentation Models,
IP(17), No. 5, May 2008, pp. 767-779.
IEEE DOI Link 0804
BibRef

Le Guyader, C.[Carole], Vese, L.A.[Luminita A.],
A Combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother,
SSVM09(600-611).
Springer DOI Link 0906
BibRef

Guillot, L.[Laurence], Le Guyader, C.[Carole],
Extrapolation of Vector Fields Using the Infinity Laplacian and with Applications to Image Segmentation,
SSVM09(87-99).
Springer DOI Link 0906
BibRef

Bentabet, L.[Layachi], Maodong, J.[Jiang],
A combined Markovian and Dirichlet sub-mixture modeling for evidence assignment: Application to image fusion,
PRL(29), No. 13, 1 October 2008, pp. 1775-1783.
WWW Version. 0804
Data fusion; Evidence theory; Mixture modeling; Dirichlet distribution; Markov fields; Iterated conditional modes BibRef

Jodouin, S.[Sylvie], Bentabet, L.[Layachi], Ziou, D.[Djemel], Vaillancourt, J.[Jean], Armenakis, C.[Costas],
A Combined Estimation-Deformation Model for Area Detection: Application to Topographic Area Feature Update,
PCV02(A: 181). 0305
BibRef

Kokkinos, I.[Iasonas], Evangelopoulos, G.[Georgios], Maragos, P.[Petros],
Texture Analysis and Segmentation Using Modulation Features, Generative Models, and Weighted Curve Evolution,
PAMI(31), No. 1, January 2009, pp. 142-157.
IEEE DOI Link 0812
BibRef
Earlier:
Advances in texture analysis- energy dominant component & multiple hypothesis testing,
ICIP04(III: 1509-1512).
IEEE DOI Link
PDF Version. 0505
BibRef
And:
Modulation-feature based textured image segmentation using curve evolution,
ICIP04(II: 1201-1204).
IEEE DOI Link
PDF Version. 0505
AM-FM texture models and Dominant Component Analysis (DCA) paradigm for feature extraction. Weighted curve evolution. BibRef

Kokkinos, I.[Iasonas], Maragos, P.[Petros],
Synergy between Object Recognition and Image Segmentation Using the Expectation-Maximization Algorithm,
PAMI(31), No. 8, August 2009, pp. 1486-1501.
IEEE DOI Link 0906
BibRef
Earlier:
An Expectation Maximization Approach to the Synergy between Image Segmentation and Object Categorization,
ICCV05(I: 617-624).
IEEE DOI Link 0510
BibRef

Evangelopoulos, G.[Georgios], Maragos, P.[Petros],
Image decomposition into structure and texture subcomponents with multifrequency modulation constraints,
CVPR08(1-8).
IEEE DOI Link 0806
BibRef
And:
Texture modulation-constrained image decomposition,
ICIP08(793-796).
IEEE DOI Link 0810
BibRef

Shaaban, K.M.[Khaled M.], Omar, N.M.[Nagwa M.],
Region-based Deformable Net for automatic color image segmentation,
IVC(27), No. 10, 2 September 2009, pp. 1504-1514.
Elsevier DOI Link
WWW Version. 0906
Deformable contours BibRef

Mahmoodi, S.,
Shape-Based Active Contours for Fast Video Segmentation,
SPLetters(16), No. 10, October 2009, pp. 857-860.
IEEE DOI Link 0907
BibRef

de Vieilleville, F.[François], Lachaud, J.O.[Jacques-Olivier],
Digital Deformable Model Simulating Active Contours,
DGCI09(203-216).
Springer DOI Link 0909
BibRef

Lachaud, J.O.[Jacques-Olivier], Vialard, A.[Anne],
Discrete Deformable Boundaries for the Segmentation of Multidimensional Images,
VF01(542 ff.).
HTML Version. 0209
BibRef

Ksantini, R.[Riadh], Shariat, F.[Farnaz], Boufama, B.S.[Boubakeur S.],
An Efficient and Fast Active Contour Model for Salient Object Detection,
CRV09(124-131).
IEEE DOI Link 0905
BibRef