8.7.1.2.2 Active Contours and Snakes, Video, Motion Segmentation Issues

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

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.
Elsevier DOI BibRef 9305
Earlier: BMVC92(xx-yy).
PDF File. 9209

See also Isoperimetric Normalization of Planar Curves. BibRef

Gevers, T.,
Robust Segmentation and Tracking of Colored Objects in Video,
CirSysVideo(14), No. 6, June 2004, pp. 776-781.
IEEE Abstract. 0407
Color based deformable model. Color constant gradients. BibRef

Gevers, T., Ghebreab, S., Smeulders, A.W.M.,
Color Invariant Snakes,
BMVC98(xx-yy). BibRef 9800

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 0106
BibRef
And:
Region-based Active Contours for Video Object Segmentation with Camera Compensation,
ICIP01(II: 61-64).
IEEE DOI 0108
BibRef
Earlier:
Detection and Tracking of Moving Objects Using a New Level Set Based Method,
ICPR00(Vol III: 1100-1105).
IEEE DOI 0009
BibRef

Jehan-Besson, S.[Stéphanie], Barlaud, M.[Michel], Aubert, G.[Gilles],
DREAM 2 S: Deformable Regions Driven by an Eulerian Accurate Minimization Method for Image and Video Segmentation,
IJCV(53), No. 1, June 2003, pp. 45-70.
DOI Link 0304
BibRef
Earlier: ECCV02(III: 365 ff.).
Springer DOI 0205

See also Object-based Motion Method for Video Coding, An.
See also Using the Shape Gradient for Active Contour Segmentation: From the Continuous to the Discrete Formulation.
See also Outer-Layer Based Tracking using Entropy as a Similarity Measure. BibRef

Roy, T.[Tristan], Debreuve, É.[Éric], Barlaud, M.[Michel], Aubert, G.[Gilles],
Segmentation of a Vector Field: Dominant Parameter and Shape Optimization,
JMIV(24), No. 2, March 2006, pp. 259-276.
Springer DOI 0605
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 0611
BibRef
Earlier: A1, A2, A4, A5, Only:
Shape gradient for multi-modal image segmentation using mutual information,
ICIP04(IV: 2729-2732).
IEEE DOI 0505

See also DREAM 2 S: Deformable Regions Driven by an Eulerian Accurate Minimization Method for Image and Video Segmentation. BibRef

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

Lecellier, F.[François], Fadili, J.[Jalal], Jehan-Besson, S.[Stéphanie], Aubert, G.[Gilles], Revenu, M.[Marinette], Saloux, E.[Eric],
Region-Based Active Contours with Exponential Family Observations,
JMIV(36), No. 1, January 2010, pp. xx-yy.
Springer DOI 1001
BibRef
Earlier: A1, A3, A2, A4, A5, A6:
Region-Based Active Contour with Noise and Shape Priors,
ICIP06(1649-1652).
IEEE DOI 0610
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 0906
BibRef
Earlier: A1, A3, A2, A5, A4:
Region-based active contours and sparse representations for texture segmentation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Cuturi, M.[Marco], Peyré, G.[Gabriel],
A Smoothed Dual Approach for Variational Wasserstein Problems,
SIIMS(9), No. 1, 2016, pp. 320-343.
DOI Link 1604
BibRef

Peyre, G.[Gabriel], Fadili, J.[Jalal], Rabin, J.[Julien],
Wasserstein active contours,
ICIP12(2541-2544).
IEEE DOI 1302
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 0311
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. 0407
BibRef
Earlier:
Tracking video objects using active contours,
Motion02(90-95).
IEEE DOI 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 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 0710
BibRef
And:
A High Dimensional Framework for Joint Color-Spatial Segmentation,
ICIP07(VI: 313-316).
IEEE DOI 0709

See also Motion and Appearance Nonparametric Joint Entropy for Video Segmentation.
See also High-Dimensional Statistical Measure for Region-of-Interest Tracking. 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).
IEEE DOI 0610
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 DOI 0312
BibRef

Cremers, D.[Daniel], Schnörr, C.[Christoph],
Statistical Shape Knowledge in Variational Motion Segmentation,
IVC(21), No. 1, January 2003, pp. 77-86.
Elsevier DOI
PDF File. 0301
BibRef
Earlier:
Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization,
DAGM02(472-480).
Springer DOI
PS File. Award, DAGM. 0303

See also Shape Statistics in Kernel Space for Variational Image Segmentation.
See also Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation. BibRef

Cremers, D.[Daniel],
A variational framework for image segmentation combining motion estimation and shape regularization,
CVPR03(I: 53-58).
IEEE DOI 0307
BibRef
And:
Statistical Shape Knowledge in Variational Image Segmentation,
Ph.D.Thesis, Department of Mathematics and Computer Science, University of Mannheim, Germany, July 2002.
PDF File. BibRef

Cremers, D.[Daniel], Soatto, S.[Stefano],
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation,
IJCV(62), No. 3, May 2005, pp. 249-265.
Springer DOI 0501
BibRef
Earlier:
Variational space-time motion segmentation,
ICCV03(886-893).
IEEE DOI 0311

See also Statistical Shape Knowledge in Variational Motion Segmentation. BibRef

Prakash, S.[Surya], Abhilash, R., Das, S.[Sukhendu],
SnakeCut: An Integrated Approach Based on Active Contour and GrabCut for Automatic Foreground Object Segmentation,
ELCVIA(6), No. 3, December 2007, pp. 13-29.
DOI Link 0801
BibRef

Prakash, S.[Surya], Das, S.[Sukhendu],
Segmenting Multiple Textured Objects Using Geodesic Active Contour and DWT,
PReMI07(111-118).
Springer DOI 0712
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 0906
Deformable contours BibRef

Shaaban, K.M.[Khaled M.], Omar, N.M.[Nagwa M.],
3D information extraction using Region-based Deformable Net for monocular robot navigation,
JVCIR(23), No. 2, February 2012, pp. 397-408.
Elsevier DOI 1201
Robot navigation; Monocular vision; Stereo vision; Correspondence problem; Video segmentation; Deformable contours; 3D information extraction; Depth information extraction BibRef

Shaaban, K.M.[Khaled M.], Omar, N.M.[Nagwa M.],
Depth extraction of partially occluded objects using deformable net,
JVCIR(39), No. 1, 2016, pp. 1-11.
Elsevier DOI 1608
Monocular vision navigation BibRef

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

Ning, J., Zhang, L., Zhang, D., Yu, W.,
Joint Registration and Active Contour Segmentation for Object Tracking,
CirSysVideo(23), No. 9, 2013, pp. 1589-1597.
IEEE DOI 1309
Active contour model BibRef

Heo, S., Koo, H.I., Cho, N.I.,
Open-Contour Tracking Using a New State-Space Model and Nonrigid Motion Training,
CirSysVideo(27), No. 11, November 2017, pp. 2355-2366.
IEEE DOI 1712
Dynamics, Object tracking, Shape, Splines (mathematics), Target tracking, Training, Nonrigid shape, omega shape tracking, open-contour tracking BibRef

Needham, T.[Tom],
Shape Analysis of Framed Space Curves,
JMIV(61), No. 8, October 2019, pp. 1154-1172.
Springer DOI 1909
elastic shape analysis approach to shape matching BibRef


Zhao, B.[Bin], Bhat, G.[Goutam], Danelljan, M.[Martin], Van Gool, L.J.[Luc J.], Timofte, R.[Radu],
Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos,
ICCV21(13536-13546)
IEEE DOI 2203
Training, Deep learning, Image segmentation, Annotations, Object segmentation, Manuals, Motion and tracking, BibRef

Oliver-Parera, M.[Maria], Muzeau, J.[Julien], Ladret, P.[Patricia], Bertolino, P.[Pascal],
Contour Detection of Multiple Moving Objects in Unconstrained Scenes using Optical Strain,
DICTA20(1-8)
IEEE DOI 2201
Adaptation models, Computational modeling, Optical computing, Optical noise, Task analysis, Optical flow, Strain, Adaptive Threshold BibRef

Lin, T., Liu, X., Li, X., Ding, E., Wen, S.,
BMN: Boundary-Matching Network for Temporal Action Proposal Generation,
ICCV19(3888-3897)
IEEE DOI 2004
feature extraction, image classification, image colour analysis, image motion analysis, Reliability BibRef

Khan, N.[Naeemullah], Sundaramoorthi, G.[Ganesh],
Learned Shape-Tailored Descriptors for Segmentation,
CVPR18(666-674)
IEEE DOI 1812
Image segmentation, Training, Measurement, Aggregates, Neural networks, Lighting BibRef

Khan, N.[Naeemullah], Hong, B.W., Yezzi, A.J.[Anthony J.], Sundaramoorthi, G.[Ganesh],
Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces,
CVPR17(1733-1742)
IEEE DOI 1711
Image segmentation, Mathematical model, Motion segmentation, Smoothing methods, Space heating BibRef

Khan, N.[Naeemullah], Algarni, M.[Marei], Yezzi, A.J.[Anthony J.], Sundaramoorthi, G.[Ganesh],
Shape-tailored local descriptors and their application to segmentation and tracking,
CVPR15(3890-3899)
IEEE DOI 1510
BibRef

Imamura, K.[Kousuke], Hiraoka, M.[Masaki], Hashimoto, H.[Hideo],
Watershed algorithm for moving object extraction considering energy minimization by snakes,
AVSBS07(534-539).
IEEE DOI 0709
BibRef
And:
Moving Object Extraction by Watershed Algorithm Considering Energy Minimization,
ACIVS07(711-719).
Springer DOI 0708
BibRef

Haseyama, M., Yokoyama, Y.,
Moving Object Extraction Using a Shape-Constraint-Based Splitting Active Contour Model,
ICIP05(III: 1260-1263).
IEEE DOI 0512
BibRef

Ciampini, R., Blanc-Féraud, L.[Laure], Barlaud, M., Salerno, E.,
Motion-based segmentation by means of active contours,
ICIP98(II: 667-670).
IEEE DOI 9810
BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Variational Models, Snake Models, Active Contours .


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