11.8.4 Nonrigid, Non-Rigid, Deformable Motion Analysis and Tracking

Kambhamettu, C., Goldgof, D.B., Terzopoulos, D., Huang, T.S.,
Nonrigid Motion Analysis,
HPRIP-CV94(405-430). BibRef 9400

Huang, W.C., and Goldgof, D.B.,
Adaptive-Size Meshes for Rigid and Nonrigid Shape Analysis and Synthesis,
PAMI(15), No. 6, June 1993, pp. 611-616.
IEEE DOI BibRef 9306
Earlier:
Adaptive-Size Physically-Based Models for Nonrigid Motion Analysis,
CVPR92(833-835).
IEEE DOI BibRef
And:
Nonrigid Motion Analysis Using Nonlinear Finite Element Modeling,
SPIE(2031), 1993, pp. 404-414. Physics Based Vision. BibRef

Huang, W.C., Goldgof, D.B., Tsap, L.V.,
Nonlinear Finite Element Methods for Nonrigid Motion Analysis,
PBMCV95(SESSION 3) BibRef 9500

Huang, W.C., Goldgof, D.B.,
Analysis of Intensity and Range Image Sequences Using Adaptive-Size Meshes,
JVCIR(4), 1993, pp. 364-381. BibRef 9300

Huang, W.C., Goldgof, D.B.,
Sampling and Surface Reconstruction with Adaptive-Size Meshes,
SPIE(1708), 1992, pp. 760-770 BibRef 9200

Tsap, L.V.[Leonid V.], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep], Huang, W.C.[Wen-Chen],
Efficient Nonlinear Finite Element Modeling of Nonrigid Objects via Optimization of Mesh Models,
CVIU(69), No. 3, March 1998, pp. 330-350.
DOI Link
See also Gesture-Tracking in Real Time with Dynamic Regional Range Computation. BibRef 9803

Tsap, L.V.[Leonid V.], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep],
Model-based force-driven nonrigid motion recovery from sequences of range images without point correspondences,
IVC(17), No. 14, 17 November 1999, pp. 997-1007.
Elsevier DOI 9911
BibRef
Earlier:
Model-based nonrigid motion recovery from sequences of range images without point correspondences,
ICIP98(II: 218-222).
IEEE DOI 9810
BibRef

Tsap, L.V.[Leonid V.], Goldgof, D.B.[Dmitry B.], and Sarkar, S.[Sudeep],
Nonrigid Motion Analysis Based on Dynamic Refinement of Finite Element Models,
PAMI(22), No. 5, May 2000, pp. 526-543.
IEEE DOI 0008
BibRef
Earlier: CVPR98(728-734).
IEEE DOI Given initial model, sparse correspondences, recover dense motion vectors. BibRef

Tsap, L.V.[Leonid V.], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep],
Fusion of physically-based registration and deformation modeling for nonrigid motion analysis,
IP(10), No. 11, November 2001, pp. 1659-1669.
IEEE DOI 0201
BibRef

Tsap, L.V.[Leonid V.], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep],
Multiscale Combination of Physically-based Registration and Deformation Modeling,
CVPR00(II: 422-429).
IEEE DOI 0005
BibRef

Zhang, Y.[Yong], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep], Tsap, L.V.[Leonid V.],
A sensitivity analysis method and its application in physics-based nonrigid motion modeling,
IVC(25), No. 3, March 2007, pp. 262-273.
Elsevier DOI 0701
BibRef
Earlier:
Tracking objects using recovered physical motion parameters,
ICPR02(II: 10-13).
IEEE DOI 0211
BibRef
Earlier:
Model-based Nonrigid Motion Analysis Using Natural Feature Adaptive Mesh,
ICPR00(Vol III: 831-835).
IEEE DOI 0009
Sensitivity analysis; Physical modeling; Nonrigid motion; Elastic parameters BibRef

Shin, M.C.[Min C.], Balasubramanian, R.[Ramprasad], Goldgof, D.B.[Dmitry B.], Kim, C.[Carlos],
Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure,
ICPR00(Vol III: 823-826).
IEEE DOI 0009
Examples track surface patches. BibRef

Koch, R.,
Dynamic 3-D Scene Analysis through Synthesis Feedback Control,
PAMI(15), No. 6, June 1993, pp. 556-568.
IEEE DOI Face analysis and reconstruction. BibRef 9306

Penna, M.A.[Michael A.],
The Incremental Approximation of Nonrigid Motion,
CVGIP(60), No. 2, September 1994, pp. 141-156.
DOI Link BibRef 9409

Penna, M.A.[Michael A.],
The Motion Analysis of Nonrigid Membranes,
CVIU(75), No. 3, September 1999, pp. 281-306. BibRef 9909

Chen, S.S.[Su-Shing], and Penna, M.A.[Michael A.],
Shape and Motion of Nonrigid Bodies,
CVGIP(36), No. 2/3, November/December 1986, pp. 175-207.
Elsevier DOI BibRef 8611
Earlier: A1 only:
Structure-from-Motion without the Rigidity Assumption,
CVWS85(105-112). Derivation and discussion of equations. BibRef

Chen, S.S.[Su-Shing], and Penna, M.A.[Michael A.],
Motion Analysis of Deformable Objects,
ACVIP1988, Chapter 6 pp. 179-220. BibRef 8800

Penna, M.A.[Michael A.],
Non-rigid Motion Analysis: Isometric Motion,
CVGIP(56), No. 3, November 1992, pp. 366-380.
Elsevier DOI Given the shape of the object, derive the motion and isometric shape changes in the object. BibRef 9211

Mishra, S.K., Goldgof, D.B., Kambhamettu, C.,
Estimating Nonrigid Motion from Point and Line Correspondences,
PRL(15), No. 6, June 1994, pp. 559-566.
See also Curvature-Based Approach to Point Correspondence Recovery in Conformal Nonrigid Motion. BibRef 9406

Chou, W.S., Chen, Y.C.,
Estimation of the Velocity Field of Two-Dimensional Deformable Motion,
PR(26), No. 2, February 1993, pp. 351-364.
Elsevier DOI BibRef 9302

Beattie, R.S., Elder, S.C.,
Sonar Image Motion Distortion Estimation And Correction Using Covariance Function Modeling,
IVC(12), No. 8, October 1994, pp. 531-535.
Elsevier DOI BibRef 9410

Chen, C.W., and Huang, T.S.[Thomas S.],
Non-Rigid Object Motion and Deformation Estimation for Three-Dimensional Data,
IJIST(2), 1990, pp. 385-394.
See also Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces. BibRef 9000

Chen, S.S., Zhao, A.G.,
Image Representation of Moving Nonrigid Objects,
JVCIR(1), 1990, pp. 199-207. BibRef 9000

Polana, R.[Ramprasad], and Nelson, R.C.[Randal C.],
Detection and Recognition of Periodic, Nonrigid Motion,
IJCV(23), No. 3, June-July 1997, pp. 261-282.
DOI Link 9708
BibRef
Earlier: A2, A1:
Recognition of Nonrigid Motion,
ARPA94(II:1219-1224). BibRef
Earlier:
Low Level Recognition of Human Motion,
Non-Rigid94(XX-YY). BibRef

Polana, R.[Ramprasad], and Nelson, R.C.[Randal C.],
Detecting Activities,
JVCIR(5), 1994, pp. 172-180. BibRef 9400
Earlier: ICPR94(A:815-818).
IEEE DOI BibRef
Earlier: CVPR93(2-7).
IEEE DOI BibRef
And: DARPA93(569-574). Recognizing activities. Finding repeated motions. BibRef

Barron, J.L., Eagleson, R.,
Recursive Estimation of Time-Varying Motion and Structure Parameters,
PR(29), No. 5, May 1996, pp. 797-818.
Elsevier DOI 9605
Recover first-order motion parameters (observer direction of translation and observer rotation), second-order motion parameters (observer rotational acceleration) and relative depth maps from time-varying optical flow. BibRef

Nastar, C.[Chahab], Ayache, N.J.[Nicholas J.],
Frequency-Based Nonrigid Motion Analysis: Application to Four Dimensional Medical Images,
PAMI(18), No. 11, November 1996, pp. 1067-1079.
IEEE DOI 9612
BibRef
Earlier:
Time representation of deformations: Combining vibration modes and Fourier analysis,
ORCV94(263-275).
Springer DOI 9412
BibRef

Nastar, C., and Ayache, N.J.,
Fast Segmentation, Tracking, and Analysis of Deformable Objects,
ICCV93(275-279).
IEEE DOI BibRef 9300
And:
Physically Based Analysis of Deformations in 3D Images,
SPIE(2031), 1993, pp. 182-192 Physics Based Vision. BibRef

Nastar, C.,
Vibration Modes for Nonrigid Motion Analysis in 3D Images,
ECCV94(A:231-236).
Springer DOI BibRef 9400

Lee, C.W., Hasegawa, O., Wongwarawipat, W., Dohi, H., Ishizuka, M.,
Realistic Image Synthesis of a Deformable Living Thing Based on Motion Understanding,
JVCIR(2), 1991, pp. 345-354. BibRef 9100

Dohi, H., Ishizuka, M.,
A 3-D vision system incorporating solid modeler and geometric reasoning,
ICPR90(I: 185-187).
IEEE DOI 9006
BibRef

Chaudhuri, S.[Subhasis], Chatterjee, S.[Shankar],
Motion Analysis of a Homogeneously Deformable Object Using Subset Correspondences,
PR(24), No. 8, 1991, pp. 739-745.
Elsevier DOI BibRef 9100
Earlier:
An Efficient, Linear, Sequential Formulation for Motion Estimation from Noisy Data,
Robust90(xx). BibRef
Earlier:
Estimation of Motion Parameters for a Deformable Object from Range Data,
CVPR89(291-295).
IEEE DOI Given matches, range, Rotation only plus deformation, find the parameters.
See also Recursive Estimation of Motion Parameters. BibRef

Collin, B.[Bertrand], Zavidovique, B.[Bertrand],
Deformation Detection with Frequency-Modulation,
PR(29), No. 8, August 1996, pp. 1385-1399.
Elsevier DOI 9608
BibRef

Denney, Jr., T.S., Prince, J.L.,
Optimal Brightness Functions for Optical Flow Estimation of Deformable Motion,
IP(3), No. 2, March 1994, pp. 178-191.
IEEE DOI BibRef 9403

Sato, Y., Moriyama, M., Hanayama, M., Naito, H., Tamura, S.,
Acquiring 3D Models of Nonrigid Moving-Objects from Time and Viewpoint Varying Image Sequences: A Step Toward Left-Ventricle Recovery,
PAMI(19), No. 3, March 1997, pp. 253-259.
IEEE DOI 9704
Time-varying 3-D shapes with a known cycle. Integrate apparent contours from different viewpoints. BibRef

Smith, P.W., Nandhakumar, N., Ramadorai, A.K.,
A Vision-Based Framework for the Discovery-Driven Manipulation of Nonrigid Objects,
AdvRob(11), No. 1, 1997, pp. 75-94. 9708
BibRef

Smith, P.W., Nandhakumar, N.,
Projective Recovery of Structure from Nonrigid Motion Using Temporal Fusion,
OptEng(36), No. 3, March 1997, pp. 755-766. 9704
BibRef

Smith, P.W., Nandhakumar, N., Ramadorai, A.K.,
Representation of Deformable Object Structure and Motion for Autonomous Manipulation Using Relative Elasticity,
SCV95(200-205).
IEEE DOI University of Virginia. BibRef 9500

Domingo, J., Ayala, G., Simo, A., de Ves, E., Martinez-Costa, L., Marco, P.,
Irregular Motion Recovery in Fluorescein Angiograms,
PRL(18), No. 8, August 1997, pp. 805-821. 9801
BibRef

Aggarwal, J.K., Cai, Q., Liao, W., Sabata, B.,
Nonrigid Motion Analysis: Articulated and Elastic Motion,
CVIU(70), No. 2, May 1998, pp. 142-156.
DOI Link BibRef 9805

Devlaminck, V.,
A Functional for Compressible or Incompressible Elastic Deformation Estimation,
SPLetters(7), No. 7, July 1999, pp. 162.
IEEE Top Reference. BibRef 9907
Earlier:
Weighting Coefficient Determination in a Displacement Estimation Functional Using the Dynamical Similarity Principle,
ICIP97(III: 622-625).
IEEE DOI BibRef

Devlaminck, V., Dubus, J.P.,
Estimation of Compressible or Incompressible Deformable Motions for Density Images,
ICIP96(I: 125-128).
IEEE DOI BibRef 9600

Toklu, C., Tekalp, A.M., Erdem, A.T.,
Semi-Automatic Video Object Segmentation in the Presence of Occlusion,
CirSysVideo(10), No. 4, June 2000, pp. 624-629.
IEEE Top Reference. 0006
BibRef

Toklu, C., Erdem, A.T., Tekalp, A.M.,
Two-Dimensional Mesh-Based Mosaic Representation for Manipulation of Video Objects with Occlusion,
IP(9), No. 9, September 2000, pp. 1617-1630.
IEEE DOI 0008
BibRef

Toklu, C., Tekalp, A.M., and Erdem, A.T.,
Simultaneous Alpha Map Generation and 2-D Mesh Tracking for Multimedia Applications,
ICIP97(I: 113-116).
IEEE DOI BibRef 9700

Erdem, A.T.[A. Tanju], Toklu, C.[Candemir],
Method for region tracking in an image sequence using a two-dimensional mesh,
US_Patent5,982,909, Nov 9, 1999
WWW Link. BibRef 9911

Toklu, C., Erdem, A.T.[A. Tanju], Sezan, M.I.[M. Ibrahim], Tekalp, A.M.[A. Murat],
2-D mesh tracking for synthetic transfiguration,
ICIP95(III: 536-539).
IEEE DOI 9510
BibRef

Erdem, A.T.[A. Tanju],
Method for generating a personalized 3-D face model,
US_Patent6,664,956, December 16, 2003.
WWW Link. BibRef 0312

Tekalp, A.M., van Beek, P., Toklu, C., Gunsel, B.,
Two-Dimensional Mesh-Based Visual-Object Representation for Interactive Synthetic/Natural Digital Video,
PIEEE(86), 1998, pp. 1029-1051. BibRef 9800

Celasun, I., Ilgaz, E., Tekalp, A.M., van Beek, P.J.L., Zhuang, N.,
Optimal hierarchical design of 2D dynamic meshes for videos,
ICIP98(II: 899-903).
IEEE DOI 9810
BibRef

Fu, Y., Erdem, A.T., Tekalp, A.M.,
Tracking Visible Boundary of Objects Using Occlusion Adaptive Motion Snake,
IP(9), No. 12, December 2000, pp. 2051-2060.
IEEE DOI 0011
BibRef

van Beek, P., Tekalp, A.M., Zhuang, N., Celasun, I., Xia, M.,
Hierarchical 2-D Mesh Representation, Tracking, and Compression for Object-Based Video,
CirSysVideo(9), No. 2, March 1999, pp. 353.
IEEE Top Reference. BibRef 9903

van Beek, P., Tekalp, A.M., and Puri, A.,
2-D Mesh Geometry and Motion Compression for Efficient Object-Based Video Representation,
ICIP97(III: 440-443).
IEEE DOI BibRef 9700

Celasun, I., Tekalp, A.M.,
Optimal 2-D Hierarchical Content-Based Mesh Design and Update for Object-Based Video,
CirSysVideo(10), No. 7, October 2000, pp. 1135-1153.
IEEE Top Reference. 0010
BibRef

Celasun, I.[Isil], Tekalp, A.M.[A. Murat], Gökçetekin, M.H.[Mete H.], Harmanci, D.M.[Derin M.],
2-D mesh-based video object segmentation and tracking with occlusion resolution,
SP:IC(16), No. 10, August 2001, pp. 949-962.
Elsevier DOI 0001
Object-based video; Video object segmentation; Object tracking; Mesh-based occlusion detection BibRef

Gokcetekin, M., Harmanci, M., Celasun, I.,
Mesh-based Segmentation and Update for Object-based Video,
ICIP00(Vol I: 343-346).
IEEE DOI 0008
BibRef

Toklu, C., Tekalp, A.M., Erdem, A.T., and Sezan, M.I.,
2D Mesh Based Tracking of Deformable Objects with Occlusion,
ICIP96(I: 933-936).
IEEE DOI 9610
BibRef

Kumar, S.[Senthil], Goldgof, D.[Dmitry],
Recovery of Global Nonrigid Motion: A Model-Based Approach without Point Correspondences,
JOSA-A(17), No. 9, September 2000, pp. 1617-1626. 0008
BibRef
Earlier: CVPR96(594-599).
IEEE DOI BibRef

Lu, C.L.[Cong-Lin], Cao, Y.[Yan], Mumford, D.[David],
Surface Evolution under Curvature Flows,
JVCIR(13), No. 1/2, March/June 2002, pp. 65-81.
DOI Link 0204
BibRef

Kambhamettu, C.[Chandra], Goldgof, D.B.[Dmitry B.],
Curvature-Based Approach to Point Correspondence Recovery in Conformal Nonrigid Motion,
CVGIP(60), No. 1, July 1994, pp. 26-43.
DOI Link BibRef 9407
Earlier:
Point Correspondence Recovery in Non-Rigid Motion,
CVPR92(222-227).
IEEE DOI Find matching points with changing volumes. BibRef

Kumar, S., Kambhamettu, C.[Chandra], Goldgof, D.B.[Dmitry B.], Sallam, M.[Maha],
Model Based Estimation of Point Correspondences between Boundaries Undergoing Nonrigid Motion,
ICIP96(I: 359-362).
IEEE DOI 9610
digital mammography application BibRef

Kambhamettu, C.[Chandra], Goldgof, D.B.[Dmitry B.], He, M.[Matthew], Laskov, P.[Pavel],
3D nonrigid motion analysis under small deformations,
IVC(21), No. 3, March 2003, pp. 229-245.
Elsevier DOI 0301
BibRef
Earlier: A1, A2, A3, Only:
Determination of Motion Parameters and Estimation of Point Correspondences in Small Nonrigid Deformations,
CVPR94(943-946).
IEEE DOI BibRef
Earlier: A1, A2, A3, Only:
On a Study of Invariant Features in Nonrigid Transformations,
WQV93(118-127). BibRef

Laskov, P.[Pavel], Kambhamettu, C.[Chandra],
Curvature-Based Algorithms for Nonrigid Motion and Correspondence Estimation,
PAMI(25), No. 10, October 2003, pp. 1349-1354.
IEEE Abstract. 0310
BibRef
Earlier:
Comparison of 3D Algorithms for Non-rigid Motion and Correspondence Estimation,
BMVC01(Poster Session 1).
HTML Version. University of Delaware 0110
Use Gaussian curvature for motion estimation without correspondence. BibRef

Yezzi, A.J.[Anthony J.], Soatto, S.[Stefano],
Deformotion: Deforming Motion, Shape Average and the Joint Registration and Approximation of Structures in Images,
IJCV(53), No. 2, July 2003, pp. 153-167.
DOI Link 0304
BibRef
Earlier: A2, A1:
DEFORMOTION: Deforming Motion, Shape Average and the Joint Registration and Segmentation of Images,
ECCV02(III: 32 ff.).
Springer DOI
PDF File. 0205
Separation of the global motion from the local deformations, using a shape average concept.
See also Modified Curvature Motion for Image Smoothing and Enhancement. BibRef

Yezzi, A.J., Soatto, S.,
Structure from motion for scenes without features,
CVPR03(I: 525-532).
IEEE DOI 0307
BibRef

You, L.H.[Li-Hua], Zhang, J.J.,
Fast generation of 3-D deformable moving surfaces,
SMC-B(33), No. 4, August 2003, pp. 616-625.
IEEE Abstract. 0308
BibRef

Vedula, S., Baker, S., Rander, P., Collins, R.T., Kanade, T.,
Three-Dimensional Scene Flow,
PAMI(27), No. 3, March 2005, pp. 475-480.
IEEE Abstract. 0501
BibRef
Earlier: ICCV99(722-729).
IEEE DOI 3-D motion of points in the world. As in OF, only normal flow can be computed directly from image measurements. Scene flow from OF and constrain structure from inconsistent optical flows in multiple cameras. BibRef

Liu, Y.H.[Yong-Huai],
Automatic 3d free form shape matching using the graduated assignment algorithm,
PR(38), No. 10, October 2005, pp. 1615-1631.
Elsevier DOI 0508
3D free-form match. K closest points. BibRef

Liu, Y.H.[Yong-Huai], Li, L.Z.[Long-Zhuang], Wang, Y.[Ying],
Free form shape matching using deterministic annealing and softassign,
ICPR04(II: 128-131).
IEEE DOI 0409
BibRef

Liu, Y.H.[Yong-Huai],
A mean field annealing approach to accurate free form shape matching,
PR(40), No. 9, September 2007, pp. 2418-2436.
Elsevier DOI 0705
Mean field annealing; Accurate matching; Overlapping free form shapes; Registration error minimisation; Weight equalisation; Overlapping area maximisation
See also Automatic Range Image Registration in the Markov Chain. BibRef

Meng, Q.G.[Qing-Gang], Li, B.H.[Bai-Hua], Holstein, H.[Horst], Liu, Y.H.[Yong-Huai],
Parameterization of point-cloud freeform surfaces using adaptive sequential learning RBFnetworks,
PR(46), No. 8, August 2013, pp. 2361-2375.
Elsevier DOI 1304
Surface parameterization; Point clouds; Adaptive sequential learning BibRef

Cao, Y.[Yan], Miller, M.I.[Michael I.], Winslow, R.L.[Raimond L.], Younes, L.[Laurent],
Large Deformation Diffeomorphic Metric Mapping of Vector Fields,
MedImg(24), No. 9, September 2005, pp. 1216-1230.
IEEE DOI 0509
BibRef
Earlier:
Large Deformation Diffeomorphic Metric Mapping of Fiber Orientations,
ICCV05(II: 1379-1386).
IEEE DOI 0510
BibRef

Glaunès, J.A.[Joan A.], Qiu, A.Q.[An-Qi], Miller, M.I.[Michael I.], Younes, L.[Laurent],
Large Deformation Diffeomorphic Metric Curve Mapping,
IJCV(80), No. 3, December 2008, pp. xx-yy.
Springer DOI 0810
BibRef

Qiu, A.Q.[An-Qi], Younes, L.[Laurent], Miller, M.I.[Michael I.],
Principal Component Based Diffeomorphic Surface Mapping,
MedImg(31), No. 2, February 2012, pp. 302-311.
IEEE DOI 1202
BibRef

Tan, M., Qiu, A.,
Large Deformation Multiresolution Diffeomorphic Metric Mapping for Multiresolution Cortical Surfaces: A Coarse-to-Fine Approach,
IP(25), No. 9, September 2016, pp. 4061-4074.
IEEE DOI 1609
biomechanics BibRef

Tan, M., Qiu, A.,
Multiscale Frame-Based Kernels for Large Deformation Diffeomorphic Metric Mapping,
MedImg(37), No. 10, October 2018, pp. 2344-2355.
IEEE DOI 1810
Kernel, Hilbert space, Brain mapping, Strain, Splines (mathematics), Multiresolution analysis, Brain mapping, multiscale kernel BibRef

Guo, H.Y.[Hong-Yu], Rangarajan, A.[Anand], Joshi, S.C.[Sarang C.], Younes, L.[Laurent],
A New Joint Clustering and Diffeomorphism Estimation Algorithm for Non-Rigid Shape Matching,
Non-Rigid04(16).
HTML Version. 0502
Match 2D nonrigid shapes, apply to corpus callosum. BibRef

Garcin, L., Rangarajan, A., Younes, L.,
Non rigid registration of shapes via diffeomorphic point matching and clustering,
ICIP04(V: 3299-3302).
IEEE DOI 0505
BibRef

Xiao, J.[Jing], Chai, J.X.[Jin-Xiang], Kanade, T.[Takeo],
A Closed-Form Solution to Non-Rigid Shape and Motion Recovery,
IJCV(67), No. 2, April 2006, pp. 233-246.
Springer DOI 0605
BibRef
Earlier: CMU-RI-TR-03-16, June, 2003.
HTML Version. 0501
BibRef

Xiao, J.[Jing], Kanade, T.[Takeo],
Uncalibrated Perspective Reconstruction of Deformable Structures,
ICCV05(II: 1075-1082).
IEEE DOI 0510
BibRef
Earlier:
Non-rigid shape and motion recovery: degenerate deformations,
CVPR04(I: 668-675).
IEEE DOI
HTML Version. 0408
BibRef

Xiao, J.[Jing], Georgescu, B.[Bogdan], Zhou, X.S.[Xiang Sean], Comaniciu, D.[Dorin], Kanade, T.[Takeo],
Simultaneous Registration and Modeling of Deformable Shapes,
CVPR06(II: 2429-2436).
IEEE DOI 0606
BibRef

Xiao, J.[Jing],
Reconstruction, Registration, and Modeling of Deformable Object Shapes,
CMU-RI-TR-05-22, May, 2005. BibRef 0505 Ph.D.Thesis.
WWW Link. BibRef

Piao, Y.[Ying], Hayakawa, K.[Kazutaka], Sato, J.[Jun],
Space-Time Invariants for Recognizing 3D Motions from Arbitrary Viewpoints under Perspective Projection,
IEICE(E89-D), No. 7, July 2006, pp. 2268-2274.
DOI Link 0607
BibRef

Yamada, T.[Takatsugu], Sato, J.[Jun],
Space-Time Moment Invariants and Recognition of Non-Rigid Motions from Arbitrary Viewpoints,
ICPR06(II: 990-993).
IEEE DOI 0609
BibRef

Brand, M.[Matthew],
Modeling shape, motion, and flexion of non-rigid 3D objects in a sequence of images,
US_Patent7,006,683, Feb 28, 2006
WWW Link. BibRef 0602

Li, M.[Min], Kambhamettu, C.[Chandra], Stone, M.[Maureen],
Nonrigid motion recovery for 3D surfaces,
IVC(25), No. 3, March 2007, pp. 250-261.
Elsevier DOI 0701
BibRef
Earlier:
Spline-based Motion Recovery for 3D Surfaces Using Nonrigid Shape Properties,
Non-Rigid04(23).
HTML Version. 0502
Nonrigid motion; Correspondence; Spline; Shape-based methods Motion and point correspondence for 3D surfaces. Shape to recover correspondences. BibRef

Roy-Chowdhury, A.K.[Amit K.],
Towards a measure of deformability of shape sequences,
PRL(28), No. 15, 1 November 2007, pp. 2164-2172.
Elsevier DOI 0711
Shape sequences; Deformations; 3D modeling BibRef

Pilet, J.[Julien], Lepetit, V.[Vincent], Fua, P.[Pascal],
Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation,
IJCV(76), No. 2, February 2008, pp. 109-122.
Springer DOI 0801
BibRef
Earlier:
Real-Time Non-Rigid Surface Detection,
CVPR05(I: 822-828).
IEEE DOI 0507
Award, CVPR. Detect and match surfaces, mesh model. BibRef

Salzmann, M.[Mathieu], Fua, P.[Pascal],
Reconstructing sharply folding surfaces: A convex formulation,
CVPR09(1054-1061).
IEEE DOI 0906
BibRef

Salzmann, M.[Mathieu], Hartley, R.I.[Richard I.], Fua, P.[Pascal],
Convex Optimization for Deformable Surface 3-D Tracking,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Moreno-Noguer, F.[Francesc], Fua, P.[Pascal],
Stochastic Exploration of Ambiguities for Nonrigid Shape Recovery,
PAMI(35), No. 2, February 2013, pp. 463-475.
IEEE DOI 1301
BibRef

Moreno-Noguer, F.[Francesc], Porta, J.M.[Josep M.], Fua, P.[Pascal],
Exploring Ambiguities for Monocular Non-Rigid Shape Estimation,
ECCV10(III: 370-383).
Springer DOI 1009
BibRef

Salzmann, M.[Mathieu], Fua, P.[Pascal],
Linear Local Models for Monocular Reconstruction of Deformable Surfaces,
PAMI(33), No. 1, January 2011, pp. 931-944.
IEEE DOI 1104
3D from single viewpoint. Resolve ambiguities based on likely deformations. BibRef

Moreno-Noguer, F.[Francesc], Salzmann, M.[Mathieu], Lepetit, V.[Vincent], Fua, P.[Pascal],
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IEEE DOI 0906
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Closed-Form Solution to Non-rigid 3D Surface Registration,
ECCV08(IV: 581-594).
Springer DOI 0810

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Salzmann, M.[Mathieu], Lepetit, V.[Vincent], Fua, P.[Pascal],
Deformable Surface Tracking Ambiguities,
CVPR07(1-8).
IEEE DOI 0706
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Monocular 3D Reconstruction of Locally Textured Surfaces,
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IEEE DOI 1205
Nonrigid 3D shape recovery. Complex lighting, partially textured surfaces. mapping from intensity to shape of local surface patches, and combine local estimates. BibRef

Ngo, D.T.[Dat Tien], Östlund, J.[Jonas], Fua, P.[Pascal],
Template-Based Monocular 3D Shape Recovery Using Laplacian Meshes,
PAMI(38), No. 1, January 2016, pp. 172-187.
IEEE DOI 1601
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Laplacian Meshes for Monocular 3D Shape Recovery,
ECCV12(III: 412-425).
Springer DOI 1210
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Salzmann, M.[Mathieu], Urtasun, R.[Raquel],
Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction,
ECCV12(IV: 245-259).
Springer DOI 1210
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Varol, A.[Aydin], Salzmann, M.[Mathieu], Fua, P.[Pascal], Urtasun, R.[Raquel],
A constrained latent variable model,
CVPR12(2248-2255).
IEEE DOI 1208
BibRef

Varol, A.[Aydin], Salzmann, M.[Mathieu], Tola, E.[Engin], Fua, P.[Pascal],
Template-free Monocular Reconstruction of Deformable Surfaces,
ICCV09(1811-1818).
IEEE DOI
PDF File. 0909
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Salzmann, M.[Mathieu], Urtasun, R.[Raquel],
Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction,
CVPR10(647-654).
IEEE DOI Video of talk:
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Non-rigid Body Interpolation Based On Generalized Morphologic Morphing,
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Estimation of mechanical parameters of deformable solids from videos,
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A Hierarchical Non-Parametric Method for Capturing Non-Rigid Deformations,
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Elsevier DOI 0811
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Earlier: CRV05(50-56).
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Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.], Kimmel, R.[Ron],
Topology-Invariant Similarity of Nonrigid Shapes,
IJCV(81), No. 3, March 2009, pp. xx-yy.
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Rock, Paper, and Scissors: Extrinsic vs. intrinsic similarity of non-rigid shapes,
ICCV07(1-6).
IEEE DOI 0710
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Shape Recognition with Spectral Distances,
PAMI(33), No. 1, January 2011, pp. 1065-1071.
IEEE DOI 1104
Similarity of nonrigid shapes based on the distributions of diffusion distances. BibRef

Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.],
Regularized Partial Matching of Rigid Shapes,
ECCV08(II: 143-154).
Springer DOI 0810
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Earlier:
Not only size matters: Regularized partial matching of nonrigid shapes,
NORDIA08(1-6).
IEEE DOI 0806
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Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.], Bruckstein, A.M.[Alfred M.], Kimmel, R.[Ron],
Partial Similarity of Objects, or How to Compare a Centaur to a Horse,
IJCV(84), No. 2, August 2009, pp. xx-yy.
Springer DOI 0906
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Paretian Similarity for Partial Comparison of Non-rigid Objects,
SSVM07(264-275).
Springer DOI 0705

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Brook, A.[Alexander], Bruckstein, A.M.[Alfred M.], Kimmel, R.[Ron],
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Zhang, S.X.[Shi-Xue], Wu, E.H.[En-Hua],
Generation Of Optimal Multiresolution Models For Deforming Mesh Sequence,
IJIG(9), No. 2, April 2009, pp. 201-215. 0905
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A Shape Feature Based Simplification Method for Deforming Meshes,
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Springer DOI 0804
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Di, H.J.[Hui-Jun], Tao, L.M.[Lin-Mi], Xu, G.Y.[Guang-You],
A Mixture of Transformed Hidden Markov Models for Elastic Motion Estimation,
PAMI(31), No. 10, October 2009, pp. 1817-1830.
IEEE DOI 0909
Elastic: non-rigid with some smoothness constraints. Eliminate ambiguity in the available interpretations. BibRef

Wang, Q.F.[Qi-Fan], Tao, L.M.[Lin-Mi], Di, H.J.[Hui-Jun],
A Globally Optimal Approach for 3D Elastic Motion Estimation from Stereo Sequences,
ECCV10(IV: 525-538).
Springer DOI 1009
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Aouada, D.[Djamila], Krim, H.[Hamid],
Squigraphs for Fine and Compact Modeling of 3-D Shapes,
IP(19), No. 2, February 2010, pp. 306-321.
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Aouada, D.[Djamila], Krim, H.[Hamid],
Meaningful 3D shape partitioning using Morse functions,
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IEEE DOI 0911
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Aouada, D.[Djamila], Dreisigmeyer, D.W.[David W.], Krim, H.[Hamid],
Geometric modeling of rigid and non-rigid 3D shapes using the global geodesic function,
NORDIA08(1-8).
IEEE DOI 0806
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Shen, S.H.[Shu-Han], Shi, W.H.[Wen-Huan], Liu, Y.C.[Yun-Cai],
Monocular 3-D Tracking of Inextensible Deformable Surfaces Under L_2-Norm,
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IEEE DOI 1002
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A fast approach to deformable surface 3D tracking,
PR(44), No. 12, December 2011, pp. 2915-2925.
Elsevier DOI 1107
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DOI Link 1111
Deformable surface 3D reconstruction; Linear programming; Convex optimization BibRef

Shen, S.H.[Shu-Han], Shi, W.H.[Wen-Huan], Liu, Y.C.[Yun-Cai],
Monocular Template-Based Tracking of Inextensible Deformable Surfaces under L2-Norm,
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Springer DOI 0909
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Shen, S.H.[Shu-Han], Ma, W., Shi, W.H.[Wen-Huan], Liu, Y.C.[Yun-Cai],
Convex Optimization for Nonrigid Stereo Reconstruction,
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IEEE DOI 1003
3-D nonrigid structure from image pair. 3-D mesh. BibRef

Lucey, S.[Simon], Wang, Y.[Yang], Saragih, J.M.[Jason M.], Cohn, J.F.[Jeffery F.],
Non-rigid face tracking with enforced convexity and local appearance consistency constraint,
IVC(28), No. 5, May 2010, pp. 781-789.
Elsevier DOI 1003
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Deformable Face Fitting with Soft Correspondence Constraints,
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IEEE DOI 0809
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Enforcing convexity for improved alignment with constrained local models,
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IEEE DOI 0806
Constrained local models; Convex quadratic fitting; Non-rigid face tracking For non-rigid alignment. BibRef

Saragih, J.M.[Jason M.], Lucey, S.[Simon], Cohn, J.F.[Jeffrey F.],
Deformable Model Fitting by Regularized Landmark Mean-Shift,
IJCV(91), No. 2, January 2011, pp. 200-215.
WWW Link. 1101
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IEEE DOI 0909
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And:
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NORDIA09(288-295).
IEEE DOI 0910
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And:
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CMU-RI-TR-09-15, May, 2009.
WWW Link. 1102
Non-rigid face fitting. Ensemble of patch based experts.
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Saragih, J.M.[Jason M.], Lucey, S.[Simon], Cohn, J.F.[Jeffrey F.],
Deformable model fitting with a mixture of local experts,
ICCV09(2248-2255).
IEEE DOI 0909
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Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.], Kimmel, R.[Ron], Mahmoudi, M.[Mona], Sapiro, G.[Guillermo],
A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching,
IJCV(89), No. 2-3, September 2010, pp. xx-yy.
Springer DOI 1006
Rather than geodesic distance (shortest path between points on the surface), the diffusion distance averages all paths connecting the points. Robust to topological changes. BibRef

Aflalo, Y.[Yonathan], Bronstein, A.M.[Alexander M.], Bronstein, M.M.[Michael M.], Kimmel, R.[Ron],
Deformable Shape Retrieval by Learning Diffusion Kernels,
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Springer DOI 1201
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Kim, T., Lee, S., Paik, J.,
Combined shape and feature-based video analysis and its application to non-rigid object tracking,
IET-IPR(5), No. 1, February 2011, pp. 87-100.
DOI Link 1103
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Jung, S., Hong, M., Choi, M.H.,
Collision handling for free-form deformation embedded surface,
IET-IPR(5), No. 4, 2011, pp. 341-348.
DOI Link 1106
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Akhter, I.[Ijaz], Sheikh, Y.[Yaser], Khan, S.[Sohaib], Kanade, T.[Takeo],
Trajectory Space: A Dual Representation for Nonrigid Structure from Motion,
PAMI(33), No. 7, July 2011, pp. 1442-1456.
IEEE DOI 1106
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In defense of orthonormality constraints for nonrigid structure from motion,
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IEEE DOI 0906
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Yang, L., Georgescu, B.[Bogdan], Zheng, Y., Wang, Y., Meer, P.[Peter], Comaniciu, D.[Dorin],
Prediction Based Collaborative Trackers (PCT): A Robust and Accurate Approach Toward 3D Medical Object Tracking,
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IEEE DOI 1111
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Example Based Non-rigid Shape Detection,
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Springer DOI 0608
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Hong, W.[Wei], Georgescu, B.[Bogdan], Zhou, X.S.[Xiang Sean], Krishnan, S.[Sriram], Ma, Y.[Yi], Comaniciu, D.[Dorin],
Database-Guided Simultaneous Multi-slice 3D Segmentation for Volumetric Data,
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Efficient Registration of Nonrigid 3-D Bodies,
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IEEE DOI 1112
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A comparison of methods for non-rigid 3D shape retrieval,
PR(46), No. 1, January 2013, pp. 449-461.
Elsevier DOI 1209
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Earlier:
SHREC'11 Track: Shape Retrieval On Non-Rigid 3d Watertight Meshes,
3DOR11(79-88)
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Survey, Non-Rigid Shape. 3D shape retrieval; Non-rigid; Benchmark BibRef

Lian, Z., Godil, A., Fabry, T., Furuya, T., Hermans, J., Ohbuchi, R., Shu, C., Smeets, D., Suetens, P., Vandermeulen, D., Wuhrer, S.,
SHREC'10 Track: Non-Rigid 3d Shape Retrieval,
EG3DOR10(101-108)
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Feature correspondences using Morse Smale complex,
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Efficient collision detection for composite finite element simulation of cuts in deformable bodies,
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Peng, Y.[Yaxin], Lin, W.[Wei], Ying, S.H.[Shi-Hui], Peng, J.G.[Ji-Gen],
Soft shape registration under lie group frame,
IET-CV(7), No. 6, December 2013, pp. 437-447.
DOI Link 1402
Lie groups BibRef

Jacobson, A.[Alec], Baran, I.[Ilya], Popovic, J.[Jovan], Sorkine-Hornung, O.[Olga],
Bounded Biharmonic Weights for Real-Time Deformation,
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Changing an object's shape is a basic operation in computer graphics. Our goal is to make the design and control of deformations simpler by allowing the user to work freely with the most convenient combination of handle types. BibRef

Zhou, Z.[Zhong], Shi, F.[Feng], Xiao, J.J.[Jiang-Jian], Wu, W.[Wei],
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IEEE DOI 1502
image motion analysis BibRef

Quiroga, J.[Julian], Devernay, F.[Frédéric], Crowley, J.L.[James L.],
Local scene flow by tracking in intensity and depth,
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Elsevier DOI 1502
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Local/global scene flow estimation,
ICIP13(3850-3854)
IEEE DOI 1402
BibRef
Earlier:
Scene flow by tracking in intensity and depth data,
HAU3D12(50-57).
IEEE DOI 1207
3D motion; Scene flow; depth data; variational BibRef

Ali, S.[Sarah], Toony, Z.[Zahra], Laurendeau, D.[Denis],
A 3D vision-based inspection method for pairwise comparison of locally deformable 3D models,
MVA(26), No. 7-8, November 2015, pp. 1061-1078.
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Yang, X., Wang, S.,
Fast deformable structure regression tracking,
IET-CV(10), No. 2, 2016, pp. 115-123.
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image classification BibRef

Zhang, S.F.[Suo-Fei], Sun, Z.X.[Zhi-Xin], Cheng, X.[Xu], Zhou, L.[Lin],
Object Tracking with Embedded Deformable Parts in Dynamic Conditional Random Fields,
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Tracking deformable parts via dynamic conditional random fields,
ICIP14(476-480)
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Computational modeling BibRef

Duffner, S.[Stefan], Garcia, C.[Christophe],
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CirSysVideo(26), No. 12, December 2016, pp. 2215-2225.
IEEE DOI 1612
BibRef
Earlier:
Exploiting Contextual Motion Cues for Visual Object Tracking,
VOT14(232-243).
Springer DOI 1504
Context. object tracking BibRef

Duffner, S.[Stefan], Garcia, C.[Christophe],
Fast Pixelwise Adaptive Visual Tracking of Non-Rigid Objects,
IP(26), No. 5, May 2017, pp. 2368-2380.
IEEE DOI 1704
Adaptation models BibRef
Earlier:
PixelTrack: A Fast Adaptive Algorithm for Tracking Non-rigid Objects,
ICCV13(2480-2487)
IEEE DOI 1403
BibRef

Hosseini, S.J.[S. Jafar], Araujo, H.[Helder],
SDP-based approach to monocular reconstruction of inextensible surfaces,
IET-CV(11), No. 1, February 2017, pp. 43-49.
DOI Link 1703
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And:
3D Estimation of Extensible Surfaces Through a Local Monocular Reconstruction Technique,
3DModelApp16(II: 114-123).
Springer DOI 1704
BibRef
Earlier:
3D Estimation of Isometric Surfaces Using a ToF-Based Approach,
ISVC14(II: 129-140).
Springer DOI 1501
non-rigid surfaces undergoing deformation BibRef

Hosseini, S.J.[S. Jafar], Araujo, H.[Helder],
Patch-based reconstruction of surfaces undergoing different types of deformations,
SIViP(11), No. 7, October 2017, pp. 1229-1236.
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Sharon, R., Francos, J.M.[Joseph M.], Hagege, R.R.[Rami R.],
Geometry and Radiometry Invariant Matched Manifold Detection,
IP(26), No. 9, September 2017, pp. 4363-4377.
IEEE DOI 1708
deformation, geometry, image classification, image representation, object detection, object recognition, object tracking, radiometry, Euclidean space, Grassmannian subspace, UME, affine geometric transformation, deformable object detection, deformable object recognition, finite dimensional family, geometric deformations, geometry-covariant, invariant object representation, matched manifold detection, monotonic amplitude transformations, monotonic radiometric transformation, nonlinear operators, object tracking framework, radiometry invariant matched manifold detection, single linear subspace-invariant, universal manifold embedding, Complexity theory, Dictionaries, Geometry, Manifolds, Orbits, Radiometry, Space vehicles, Distance learning, image analysis, matched filters, object, detection BibRef

Cohen, G.[Gilad], Francos, J.M.[Joseph M.], Hagege, R.R.[Rami R.],
Joint segmentation and registration of elastically deformable objects,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Varano, V.[Valerio], Gabriele, S.[Stefano], Teresi, L.[Luciano], Dryden, I.L.[Ian L.], Puddu, P.E.[Paolo E.], Torromeo, C.[Concetta], Piras, P.[Paolo],
The TPS Direct Transport: A New Method for Transporting Deformations in the Size-and-Shape Space,
IJCV(124), No. 3, September 2017, pp. 384-408.
Springer DOI 1708
Compare small shape changes. BibRef

Yang, J., Guo, D., Li, K., Wu, Z., Lai, Y.,
Global 3D Non-Rigid Registration of Deformable Objects Using a Single RGB-D Camera,
IP(28), No. 10, October 2019, pp. 4746-4761.
IEEE DOI 1909
image registration, solid modelling, single RGB-D camera, nonrigid deformations, high-quality results, surface reconstruction BibRef

Gao, Y.[Yuan], Yuille, A.L.[Alan L.],
Estimation of 3D Category-Specific Object Structure: Symmetry, Manhattan and/or Multiple Images,
IJCV(127), No. 10, October 2019, pp. 1501-1526.
Springer DOI 1909
BibRef
Earlier:
Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images,
CVPR17(6718-6727)
IEEE DOI 1711
BibRef
Earlier:
Symmetric Non-rigid Structure from Motion for Category-Specific Object Structure Estimation,
ECCV16(II: 408-424).
Springer DOI 1611
Automobiles, Cameras, Estimation, Image reconstruction, Periodic structures, BibRef

Chu, L.[Lutao], Li, H.[Huiyun], Yang, Z.H.[Zhi-Heng],
Accurate scale estimation for visual tracking with significant deformation,
IET-CV(14), No. 5, August 2020, pp. 278-287.
DOI Link 2007
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Hu, S.F.[Shan-Feng], Shum, H.P.H.[Hubert P. H.], Aslam, N.[Nauman], Li, F.W.B.[Frederick W. B.], Liang, X.O.[Xia-Ohui],
A Unified Deep Metric Representation for Mesh Saliency Detection and Non-Rigid Shape Matching,
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IEEE DOI 2008
Shape, Measurement, Saliency detection, Strain, Task analysis, Mesh saliency, recurrent neural network BibRef

Chen, Y.[Yu], Zhao, J.Y.[Jie-Yu], Shi, C.W.[Cong-Wei], Yuan, D.D.[Dong-Dong],
Mesh Convolution: A Novel Feature Extraction Method for 3D Nonrigid Object Classification,
MultMed(23), 2021, pp. 3098-3111.
IEEE DOI 2109
Solid modeling, Shape, Convolution, Computational modeling, Feature extraction, Analytical models, spatial co-occurrence information BibRef

Bai, F.[Fang], Bartoli, A.E.[Adrien E.],
Procrustes Analysis with Deformations: A Closed-Form Solution by Eigenvalue Decomposition,
IJCV(130), No. 2, February 2022, pp. 567-593.
Springer DOI 2202
Bringing multiple shapes into a common reference by estimating transformations. BibRef

Tajdari, F.[Farzam], Huysmans, T.[Toon], Yang, Y.S.[Yu-Sheng], Song, Y.[Yu],
Feature Preserving Non-Rigid Iterative Weighted Closest Point and Semi-Curvature Registration,
IP(31), 2022, pp. 1841-1856.
IEEE DOI 2202
Surface treatment, Cost function, Shape, Strain, Robustness, Minimization, Non-rigid registration, curvature, non-linearity, region of attraction BibRef

Badias, A.[Alberto], Alfaro, I.[Iciar], Gonzalez, D.[David], Chinesta, F.[Francisco], Cueto, E.[Elías],
MORPH-DSLAM: Model Order Reduction for Physics-Based Deformable SLAM,
PAMI(44), No. 11, November 2022, pp. 7764-7777.
IEEE DOI 2210
Shape, Physics, Strain, Solids, Simultaneous localization and mapping, augmented reality, machine learning BibRef

Wu, S.Z.[Shang-Zhe], Rupprecht, C.[Christian], Vedaldi, A.[Andrea],
Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild,
PAMI(45), No. 4, April 2023, pp. 5268-5281.
IEEE DOI 2303
(Invited Paper). BibRef
Earlier: CVPR20(1-10)
IEEE DOI 2008
Award, CVPR. Faces, Shape, Image reconstruction, Solid modeling, Lighting, Training, Unsupervised 3D reconstruction, single-image 3D reconstruction, intrinsic image decomposition. Shape, Training BibRef

Zeng, H.T.[Hai-Tian], Yu, X.[Xin], Miao, J.X.[Jia-Xu], Yang, Y.[Yi],
MHR-Net: Multiple-Hypothesis Reconstruction of Non-Rigid Shapes from 2D Views,
ECCV22(II:1-17).
Springer DOI 2211
BibRef

Novotny, D.[David], Rocco, I.[Ignacio], Sinha, S.[Samarth], Carlier, A.[Alexandre], Kerchenbaum, G.[Gael], Shapovalov, R.[Roman], Smetanin, N.[Nikita], Neverova, N.[Natalia], Graham, B.[Benjamin], Vedaldi, A.[Andrea],
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos,
CVPR22(5585-5594)
IEEE DOI 2210
Deformable models, Solid modeling, Structure from motion, Heuristic algorithms, Dynamics, Sensor systems, 3D from multi-view and sensors BibRef

Chen, R.H.[Rong-Han], Cong, Y.[Yang], Dong, J.H.[Jia-Hua],
Unsupervised Dense Deformation Embedding Network for Template-Free Shape Correspondence,
ICCV21(8341-8350)
IEEE DOI 2203
Deep learning, Shape, Annotations, Cognition, Decoding, Transfer/Low-shot/Semi/Unsupervised Learning, Vision applications and systems BibRef

Li, Y.[Yang], Takehara, H.[Hikari], Taketomi, T.[Takafumi], Zheng, B.[Bo], Nießner, M.[Matthias],
4DComplete: Non-Rigid Motion Estimation Beyond the Observable Surface,
ICCV21(12686-12696)
IEEE DOI 2203
Geometry, Training, Shape, Tracking, Motion estimation, Humanoid robots, 3D from a single image and shape-from-x, Stereo, 3D from multiview and other sensors BibRef

Ginzburg, D.[Dvir], Raviv, D.[Dan],
Dual Geometric Graph Network (DG2N) Iterative Network for Deformable Shape Alignment,
3DV21(1341-1350)
IEEE DOI 2201
Point cloud compression, Deformable models, Shape, Computational modeling, Geometric modeling, Deep learning, iterative deep learning BibRef

Eisenberger, M.[Marvin], Novotny, D.[David], Kerchenbaum, G.[Gael], Labatut, P.[Patrick], Neverova, N.[Natalia], Cremers, D.[Daniel], Vedaldi, A.[Andrea],
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go,
CVPR21(7469-7479)
IEEE DOI 2111
A smooth interpolation and point-to-point correspondences between them. Training, Interpolation, Shape, Neural networks, Manuals, Feature extraction BibRef

Hahner, S.[Sara], Attaiki, S.[Souhaib], Garcke, J.[Jochen], Ovsjanikov, M.[Maks],
Unsupervised Representation Learning for Diverse Deformable Shape Collections,
3DV24(1594-1604)
IEEE DOI Code:
WWW Link. 2408
Representation learning, Learning systems, Interpolation, Codes, Shape, Encoding, Representation Learning, Surface Mesh Autoencoder, Mesh Pooling BibRef

Attaiki, S.[Souhaib], Pai, G.[Gautam], Ovsjanikov, M.[Maks],
DPFM: Deep Partial Functional Maps,
3DV21(175-185)
IEEE DOI 2201
(Page number seems wrong, pages duplicated with another one.) Manifolds, Learning systems, Codes, Shape, Benchmark testing, Robustness, Shape Matching, Partial Shape Matching, Functional Maps BibRef

Pai, G.[Gautam], Ren, J.[Jing], Melzi, S.[Simone], Wonka, P.[Peter], Ovsjanikov, M.[Maks],
Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence with Functional Maps,
CVPR21(384-393)
IEEE DOI 2111
Visualization, Shape, Filtering algorithms, Iterative algorithms, Complexity theory, Pattern recognition BibRef

Moynihan, M.[Matthew], Ruano, S.[Susana], Pagés, R.[Rafael], Smolic, A.[Aljosa],
Autonomous Tracking For Volumetric Video Sequences,
WACV21(1659-1668)
IEEE DOI 2106
Industries, Geometry, Target tracking, Video sequences, Topology BibRef

Pedone, M.[Matteo], Mostafa, A.[Abdelrahman], Heikkilä, J.[Janne],
Learning non-rigid surface reconstruction from spatia-temporal image patches,
ICPR21(10134-10140)
IEEE DOI 2105
Training, Surface reconstruction, Structure from motion, Databases, Shape, Video sequences BibRef

Harsch, L.[Lukas], Burgbacher, J.[Johannes], Riedelbauch, S.[Stefan],
Transferable Model for Shape Optimization subject to Physical Constraints,
ICPR21(5091-5098)
IEEE DOI 2105
Geometry, Solid modeling, Shape, Computational modeling, Neural networks, Transforms BibRef

Ishimtsev, V.[Vladislav], Bokhovkin, A.[Alexey], Artemov, A.[Alexey], Ignatyev, S.[Savva], Niessner, M.[Matthias], Zorin, D.[Denis], Burnaev, E.[Evgeny],
CAD-deform: Deformable Fitting of CAD Models to 3D Scans,
ECCV20(XIII:599-628).
Springer DOI 2011
BibRef

Agudo, A.[Antonio],
Total Estimation from RGB Video: On-line Camera Self-Calibration, Non-Rigid Shape and Motion,
ICPR21(8140-8147)
IEEE DOI 2105
Deformable models, Optical filters, Shape, Training data, Estimation, Cameras BibRef

Agudo, A.,
Segmentation and 3D Reconstruction of Non-Rigid Shape from RGB Video,
ICIP20(2845-2849)
IEEE DOI 2011
Shape, Cameras, Strain, Tracking, Radio frequency, Optimization BibRef

Ginzburg, D.[Dvir], Raviv, D.[Dan],
Cyclic Functional Mapping: Self-supervised Correspondence Between Non-isometric Deformable Shapes,
ECCV20(V:36-52).
Springer DOI 2011
BibRef

Park, S.[Sungheon], Lee, M.[Minsik], Kwak, N.[Nojun],
Procrustean Regression Networks: Learning 3d Structure of Non-rigid Objects from 2d Annotations,
ECCV20(XXIX: 1-18).
Springer DOI 2010
BibRef

Roetzer, P.[Paul], Swoboda, P.[Paul], Cremers, D.[Daniel], Bernard, F.[Florian],
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching,
CVPR22(428-438)
IEEE DOI 2210
Codes, Shape, Integer linear programming, Pattern recognition, Optimization, grouping and shape analysis, Optimization methods, Segmentation BibRef

Abbas, A.[Ahmed], Swoboda, P.[Paul],
FastDOG: Fast Discrete Optimization on GPU,
CVPR22(439-449)
IEEE DOI 2210
Perturbation methods, Graphics processing units, Prototypes, Parallel processing, Prediction algorithms, Inference algorithms, Optimization methods BibRef

Bernard, F., Suri, Z.K., Theobalt, C.,
MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment,
CVPR20(13823-13832)
IEEE DOI 2008
Shape, Strain, Deformable models, Programming, Optimization, Frequency modulation BibRef

Örnhag, M.V., Olsson, C., Heyden, A.,
Bilinear Parameterization For Differentiable Rank-Regularization,
DynaVis20(1416-1425)
IEEE DOI 2008
Convergence, Structure from motion, Robustness, Optimization, Standards, Deformable models BibRef

Li, Y., Božic, A., Zhang, T., Ji, Y., Harada, T., Nießner, M.,
Learning to Optimize Non-Rigid Tracking,
CVPR20(4909-4917)
IEEE DOI 2008
Feature extraction, Tracking, Strain, Convergence, Optimization, Task analysis, Image color analysis BibRef

Wang, Y.F.[Yi-Fan], Aigerman, N.[Noam], Kim, V.G.[Vladimir G.], Chaudhuri, S.[Siddhartha], Sorkine-Hornung, O.[Olga],
Neural Cages for Detail-Preserving 3D Deformations,
CVPR20(72-80)
IEEE DOI 2008
Shape, Strain, Interpolation, Training, Neural networks, Task analysis BibRef

Nascimento, E.R., Potje, G., Martins, R., Chamone, F., Campos, M., Bajcsy, R.,
GEOBIT: A Geodesic-Based Binary Descriptor Invariant to Non-Rigid Deformations for RGB-D Images,
ICCV19(10003-10011)
IEEE DOI 2004
differential geometry, feature extraction, image colour analysis, image matching, image texture, object tracking, Image recognition BibRef

Wang, T., Ling, H., Lang, C., Feng, S., Hou, X.,
Deformable Surface Tracking by Graph Matching,
ICCV19(901-910)
IEEE DOI 2004
feature extraction, graph theory, image enhancement, image matching, image reconstruction, image texture, Surface texture BibRef

Lee, J.[Junesuk], Kim, E.S.[Eung-Su], Park, S.Y.[Soon-Yong],
3D Non-rigid Registration of Deformable Object Using GPU,
IbPRIA19(I:610-619).
Springer DOI 1910
BibRef

Yu, R.X.[Rui-Xuan], Sun, J.[Jian], Li, H.B.[Hui-Bin],
Learning Spectral Transform Network on 3D Surface for Non-rigid Shape Analysis,
DeepLearn-G18(III:377-394).
Springer DOI 1905
BibRef

Dabral, R.[Rishabh], Mughal, M.H.[Muhammad Hamza], Golyanik, V.[Vladislav], Theobalt, C.[Christian],
MoFusion: A Framework for Denoising-Diffusion-Based Motion Synthesis,
CVPR23(9760-9770)
IEEE DOI 2309
BibRef

Tretschk, E.[Edgar], Tewari, A.[Ayush], Golyanik, V.[Vladislav], Zollhöfer, M.[Michael], Lassner, C.[Christoph], Theobalt, C.[Christian],
Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video,
ICCV21(12939-12950)
IEEE DOI 2203
Dynamics, Bending, Rendering (computer graphics), Cameras, Rigidity, Task analysis, 3D from a single image and shape-from-x, BibRef

Habermann, M.[Marc], Xu, W.P.[Wei-Peng], Rhodin, H.[Helge], Zollhöfer, M.[Michael], Pons-Moll, G.[Gerard], Theobalt, C.[Christian],
NRST: Non-rigid Surface Tracking from Monocular Video,
GCPR18(335-348).
Springer DOI 1905
BibRef

Probst, T.[Thomas], Chhatkuli, A.[Ajad], Paudel, D.P.[Danda Pani], Van Gool, L.J.[Luc J.],
Model-free Consensus Maximization for Non-Rigid Shapes,
ECCV18(II: 123-140).
Springer DOI 1810
BibRef

Bugaev, B.[Bogdan], Kryshchenko, A.[Anton], Belov, R.[Roman],
Combining 3D Model Contour Energy and Keypoints for Object Tracking,
ECCV18(XII: 55-70).
Springer DOI 1810
BibRef

Han, W., Huang, G.B., Cui, D.,
Deformable and Occluded Object Tracking via Graph Learning,
DICTA17(1-8)
IEEE DOI 1804
graph theory, image segmentation, learning (artificial intelligence), object tracking, Visualization BibRef

Zafeiriou, S.P.[Stefanos P.], Matas, J.G.[Jiri G.],
From active appearance models and mnemonic descent to 3d morphable models: A brief history of statistical deformable models with examples in menpo,
IPTA16(1-2)
IEEE DOI 1703
BibRef

Eynard, D.[Davide], Rodolà, E.[Emanuele], Glashoff, K.[Klaus], Bronstein, M.M.[Michael M.],
Coupled Functional Maps,
3DV16(399-407)
IEEE DOI 1701
image matching BibRef

Cosmo, L., Rodolà, E.[Emanuele], Masci, J., Torsello, A., Bronstein, M.M.[Michael M.],
Matching Deformable Objects in Clutter,
3DV16(1-10)
IEEE DOI 1701
image matching BibRef

Tsoli, A., Argyros, A.A.,
Tracking Deformable Surfaces That Undergo Topological Changes Using an RGB-D Camera,
3DV16(333-341)
IEEE DOI 1701
cameras BibRef

Corring, J.[John], Rangarajan, A.[Anand],
Resonant Deformable Matching: Simultaneous Registration and Reconstruction,
ECCV16(VI: 51-68).
Springer DOI 1611
BibRef

Yumer, M.E.[M. Ersin], Mitra, N.J.[Niloy J.],
Learning Semantic Deformation Flows with 3D Convolutional Networks,
ECCV16(VI: 294-311).
Springer DOI 1611
BibRef

Zhang, P.B., Hung, Y.S.,
Non-Rigid Structure from Motion through Estimation of Blend Shapes,
DICTA15(1-7)
IEEE DOI 1603
affine transforms BibRef

Abbasnejad, I.[Iman], Sridharan, S.[Sridha], Denman, S.[Simon], Fookes, C.[Clinton], Lucey, S.[Simon],
From Affine Rank Minimization Solution to Sparse Modeling,
WACV17(501-509)
IEEE DOI 1609
Compressed sensing, Context, Histograms, Image coding, Indexes, Minimization, Support, vector, machines BibRef

Valmadre, J.[Jack], Sridharan, S.[Sridha], Denman, S.[Simon], Fookes, C.[Clinton], Lucey, S.[Simon],
Closed-Form Solutions for Low-Rank Non-Rigid Reconstruction,
DICTA15(1-6)
IEEE DOI 1603
image motion analysis BibRef

Feng, J.[Jian], Won, I.S.[In-Su], Jeong, J.H.[Jae-Hyup], Jeong, D.S.[Dong-Seok],
Rigid and non-rigid object image matching using deformable object image discrimination,
FCV15(1-4)
IEEE DOI 1506
computational complexity BibRef

Newcombe, R.A.[Richard A.], Fox, D.[Dieter], Seitz, S.M.[Steven M.],
DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time,
CVPR15(343-352)
IEEE DOI 1510
Award, CVPR. BibRef

Corman, É.[Étienne], Ovsjanikov, M.[Maks], Chambolle, A.[Antonin],
Supervised Descriptor Learning for Non-Rigid Shape Matching,
NORDIA14(283-298).
Springer DOI 1504
BibRef

Wang, W.[Wei], Burschka, D.[Darius],
Dense and Deformable Motion Extraction in Dynamic Scenes Based on Hierarchical MRF Optimization in RGB-D Images,
WACV15(1115-1122)
IEEE DOI 1503
Data mining BibRef

Hur, J.[Junhwa], Lim, H.[Hwasup], Park, C.S.[Chang-Soo], Ahn, S.C.[Sang Chul],
Generalized Deformable Spatial Pyramid: Geometry-preserving dense correspondence estimation,
CVPR15(1392-1400)
IEEE DOI 1510
BibRef
Earlier: A1, A2, A4, Only:
3D Deformable Spatial Pyramid for Dense 3D Motion Flow of Deformable Object,
ISVC14(I: 118-127).
Springer DOI 1501

See also Deformable Spatial Pyramid Matching for Fast Dense Correspondences. BibRef

Zhu, Y.Y.[Ying-Ying], Huang, D.[Dong], de la Torre, F.[Fernando], Lucey, S.[Simon],
Complex Non-rigid Motion 3D Reconstruction by Union of Subspaces,
CVPR14(1542-1549)
IEEE DOI 1409
BibRef

Liu, K.[Kangwei], Zhang, J.[Junge], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Deformable Object Matching via Deformation Decomposition Based 2D Label MRF,
CVPR14(2321-2328)
IEEE DOI 1409
Markov Random Field BibRef

Ali, S., Tran, T.T., Cao, V.T.[Van-Toan], Laurendeau, D.,
An Approach for Local Comparison of Deformable 3D Models,
ACPR13(852-856)
IEEE DOI 1408
solid modelling BibRef

Sipiran, I.[Ivan], Bustos, B.[Benjamin],
A Fully Hierarchical Approach for Finding Correspondences in Non-rigid Shapes,
ICCV13(817-824)
IEEE DOI 1403
Correspondences; Non-rigid shapes; shape matching BibRef

Liu, Y.[Ye], Chen, Y.Q.[Yan Qiu],
3D tracking of deformable surface by propagating feature correspondences,
ICPR12(2202-2205).
WWW Link. 1302
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Biasotti, S., Bai, X., Bustos, B., Cerri, A., Giorgi, D., Li, L., Mortara, M., Sipiran, I., Zhang, S., Spagnuolo, M.,
SHREC'12 Track: Stability on Abstract Shapes,
3DOR12(101-107)
DOI Link 1301
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Wuhrer, S.[Stefanie], Lang, J.[Jochen], Shu, C.[Chang],
Tracking Complete Deformable Objects with Finite Elements,
3DIMPVT12(1-8).
IEEE DOI 1212
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Aziz, F.[Furqan], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Shape Analysis Using the Edge-Based Laplacian,
SSSPR12(382-390).
Springer DOI 1211
Versus vertex-based Laplacian. BibRef

Beeler, T.[Thabo], Bradley, D.[Derek], Zimmer, H.[Henning], Gross, M.[Markus],
Improved Reconstruction of Deforming Surfaces by Cancelling Ambient Occlusion,
ECCV12(I: 30-43).
Springer DOI 1210
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Li, B.[Bo], Godil, A.[Afzal], Johan, H.[Henry],
Non-rigid and Partial 3d Model Retrieval Using Hybrid Shape Descriptor and Meta Similarity,
ISVC12(I: 199-209).
Springer DOI 1209
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Mahmoodi, S.[Sasan], Al-Huseiny, M.S.[Muayed S.], Nixon, M.S.[Mark S.],
Similarity Registration for Shapes Based on Signed Distance Functions,
ISVC12(I: 599-609).
Springer DOI 1209
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Jokinen, O., Haggrén, H.,
Detection and Correction of Changes In Exterior and Interior Orientations While Estimating 3-d Object Deformations From Multiple Images With Weak Or Strong Imaging Geometry,
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DOI Link 1209
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Unger, M.[Markus], Werlberger, M.[Manuel], Pock, T.[Thomas], Bischof, H.[Horst],
Joint motion estimation and segmentation of complex scenes with label costs and occlusion modeling,
CVPR12(1878-1885).
IEEE DOI 1208
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Zeng, W.[Wei], Gu, X.F.D.[Xian-Feng David],
3D dynamics analysis in Teichmüller space,
4DMOD11(1610-1617).
IEEE DOI 1201
2D model generalized to 3D. BibRef

Liu, Y.[Ye], Chen, Y.Q.[Yan Qiu],
Joint reconstruction of 3D shape and non-rigid motion in a region-growing framework,
4DMOD11(1578-1585).
IEEE DOI 1201
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Tsoli, A.[Aggeliki], Black, M.J.[Michael J.],
Shape- and Pose-Invariant Correspondences Using Probabilistic Geodesic Surface Embedding,
DAGM11(256-265).
Springer DOI 1109
Non rigid, deformable matching. Use Geodesic distances. BibRef

Yao, X.F.[Xu-Feng], Song, Z.J.[Zhi-Jian],
Deformable Registration for Geometric Distortion Correction of Diffusion Tensor Imaging,
CAIP11(I: 545-553).
Springer DOI 1109
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Moll, M.[Markus], Van Gool, L.J.[Luc J.],
Optimal Templates for Nonrigid Surface Reconstruction,
ECCV12(I: 696-709).
Springer DOI 1210
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Earlier:
Separating rigid motion from linear local deformation models,
NORDIA11(37-44).
IEEE DOI 1106
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Julià, C.[Carme], Paladini, M.[Marco], Garg, R.[Ravi], Puig, D.[Domenec], Agapito, L.[Lourdes],
Automatic Estimation of the Number of Deformation Modes in Non-rigid SfM with Missing Data,
SCIA11(381-392).
Springer DOI 1105
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Zheng, Y.Q.[Yin-Qiang], Sugimoto, S.[Shigeki], Okutomi, M.[Masatoshi],
3D Structure Refinement of Nonrigid Surfaces through Efficient Image Alignment,
ACCV10(IV: 76-89).
Springer DOI 1011
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Su, Y.Q.[Yuan-Qi], Liu, Y.H.[Yue-Hu], Yang, Y.[Yang],
Optimal Trajectory Space Finding for Nonrigid Structure from Motion,
ACIVS10(I: 357-366).
Springer DOI 1012
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Wang, X.L.[Xu-Lei], Liu, Y.[Yi], Zha, H.B.[Hong-Bin],
Intrinsic Spin Images: A subspace decomposition approach to understanding 3D deformable shapes,
3DPVT10(xx-yy).
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Xiong, P.F.[Peng-Fei], Huang, L.[Lei], Liu, C.P.[Chang-Ping],
Initialization and Pose Alignment in Active Shape Model,
ICPR10(3971-3974).
IEEE DOI 1008
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Wang, C.H.[Chen-Hao], Li, X.[Xiong], Liu, Y.C.[Yun-Cai],
Monocular 3D Tracking of Deformable Surfaces Using Linear Programming,
ICPR10(1710-1713).
IEEE DOI 1008
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Popham, T.[Thomas], Bhalerao, A.H.[Abhir H.], Wilson, R.[Roland],
Multi-frame Scene-flow Estimation Using a Patch Model and Smooth Motion Prior,
BMVCWS10(xx-yy).
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Popham, T.[Thomas], Wilson, R.[Roland], Bhalerao, A.H.[Abhir H.],
A smooth 6DOF motion prior for efficient 3D surface tracking,
3DTV10(1-4).
IEEE DOI 1006
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Tunc, B., Zhou, S.K., Park, J.H., Gokmen, M.,
Context ranking machine and its application to rigid localization of deformable objects,
ICIP09(3633-3636).
IEEE DOI 0911
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Chan, Y.H.[Yuk Hin], Strozzi, A.G., Lau, A., Gong, R.[Rui], Delmas, P., Gimel'farb, G.L., Marquez, J.,
Modelling of elastic deformation using stereo vision and smoothed particle hydrodynamics,
IVCNZ09(352-356).
IEEE DOI 0911
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Jung, C.K.[Cheol-Kon], Kim, J.K.[Joong-Kyu],
Automatic Segmentation of Non-rigid Objects in Image Sequences Using Spatiotemporal Information,
PSIVT09(562-573).
Springer DOI 0901
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Rabaud, V.[Vincent], Belongie, S.J.[Serge J.],
Linear embeddings in non-rigid structure from motion,
CVPR09(2427-2434).
IEEE DOI 0906
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Earlier:
Re-thinking non-rigid structure from motion,
CVPR08(1-8).
IEEE DOI 0806
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Shaji, A.[Appu], Varol, A.[Aydin], Fua, P.[Pascal], Yashoteja, Jain, A.[Ankush], Chandran, S.[Sharat],
Resolving occlusion in multiframe reconstruction of deformable surfaces,
NORDIA11(31-36).
IEEE DOI 1106
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Shaji, A.[Appu], Varol, A.[Aydin], Torresani, L.[Lorenzo], Fua, P.[Pascal],
Simultaneous point matching and 3D deformable surface reconstruction,
CVPR10(1221-1228).
IEEE DOI 1006
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Shaji, A.[Appu], Chandran, S.[Sharat],
Riemannian manifold optimisation for non-rigid structure from motion,
NORDIA08(1-6).
IEEE DOI 0806
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Hilsmann, A.[Anna], Eisert, P.[Peter],
Tracking deformable surfaces with optical flow in the presence of self occlusion in monocular image sequences,
NORDIA08(1-6).
IEEE DOI 0806
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Zhang, J.,
Statistical Modeling and Localization of Nonrigid and Articulated Shapes,
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Wu, J.J.[Jia Jane],
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Syrkina, E.[Ekaterina], Gonzalez Ballester, M.A.[Miguel A.], Szekely, G.[Gabor],
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MMBIA07(1-7).
IEEE DOI 0710
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El Abed, A.[Abir], Dubuisson, S.[Séverine], Béréziat, D.[Dominique],
Energetic Particle Filter for Online Multiple Target Tracking,
ICIP07(I: 493-496).
IEEE DOI 0709
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And:
ENMIM: Energetic Normalized Mutual Information Model for Online Multiple Object Tracking with Unlearned Motions,
ACIVS07(955-967).
Springer DOI 0708
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Earlier:
Comparison of Statistical and Shape-Based Approaches for Non-rigid Motion Tracking with Missing Data Using a Particle Filter,
ACIVS06(185-196).
Springer DOI 0609
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Mullally, W.[William], Betke, M.[Margrit], Bellardine, C.[Carissa], Lutchen, K.[Kenneth],
Locally Switching Between Cost Functions in Iterative Non-rigid Registration,
CVBIA05(367-377).
Springer DOI 0601
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Llado, X.[Xavier], del Bue, A.[Alessio], Agapito, L.[Lourdes],
Recovering Euclidean deformable models from stereo-motion,
ICPR08(1-4).
IEEE DOI 0812
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Earlier:
Euclidean Reconstruction of Deformable Structure Using a Perspective Camera with Varying Intrinsic Parameters,
ICPR06(I: 139-142).
IEEE DOI 0609
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Smeraldi, F., del Bue, A.[Alessio], Agapito, L.[Lourdes],
Tracking Points on Deformable Objects with Ranklets,
ICIP05(III: 121-124).
IEEE DOI 0512
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Lim, J.W.[Jong-Woo], Yang, M.H.[Ming-Hsuan],
A Direct Method for Modeling Non-Rigid Motion with Thin Plate Spline,
CVPR05(I: 1196-1202).
IEEE DOI 0507
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Gómez, J.I.[José I.], de la Blanca, N.P.[Nicolás Pérez],
Labeling Still Image Databases Using Graphical Models,
IbPRIA09(330-337).
Springer DOI 0906
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Marín-Jiménez, M.J.[Manuel J.], de la Blanca, N.P.[Nicolás Pérez], Gómez, J.I.[José I.],
Locating and Segmenting 3D Deformable Objects by Using Clusters of Contour Fragments,
IbPRIA07(I: 402-409).
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Marín-Jiménez, M.J.[Manuel J.], Pérez de la Blanca, N.[Nicolás],
Sharing Visual Features for Animal Categorization: An Empirical Study,
ICIAR06(II: 13-22).
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Marín-Jiménez, M.J.[Manuel J.], de la Blanca, N.P.[Nicolás Pérez],
Empirical Study of Multi-scale Filter Banks for Object Categorization,
ICPR06(I: 578-581).
IEEE DOI 0609
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Matching Deformable Features Based on Oriented Multi-scale Filter Banks,
AMDO06(336-345).
Springer DOI 0607
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de la Blanca, N.P.[Nicolás Pérez], Fuertes, J.M.[José M.], Lucena, M.J.[Manuel J.],
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IbPRIA05(I:251).
Springer DOI 0509
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Earlier:
Deformable Object Matching Based on Multi-scale Local Histograms,
AMDO04(154-162).
Springer DOI 0505

See also Human Action Recognition Using Optical Flow Accumulated Local Histograms. BibRef

Lucena, M.J.[Manuel J.], Fuertes, J.M.[José M.], de la Blanca, N.P.[Nicolás Pérez],
Real-Time Tracking Using Multiple Target Models,
IbPRIA05(I:20).
Springer DOI 0509
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Lucena, M.J., Fuertes, J.M., de la Blanca, N.P.[N. Perez], Garrido, A.,
Using Optical Flow as Evidence for Probabilistic Tracking,
SCIA03(1044-1049).
Springer DOI 0310
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An optical flow probabilistic observation model for tracking,
ICIP03(III: 957-960).
IEEE DOI 0312
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Lucena, M.J.[Manuel J.], Fuertes, J.M.[José Manuel], de la Blanca, N.P.[Nicolás Pérez],
Evaluation of three optical flow-based observation models for tracking,
ICPR04(IV: 236-239).
IEEE DOI 0409
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de la Blanca, N.P.[Nicolás Pérez], Garrido, A.[Antonio],
Recovering Non-rigid 3D Shape Using a Plane+Parallax Approach,
AMDO02(251 ff.).
Springer DOI 0303
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Non-Rigid Motion Estimation Using the Robust Tensor Method,
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Compact Representations for Fast Nonrigid Registration of Medical Images,
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Shinya, M.[Mikio],
Unifying measured point sequences of deforming objects,
3DPVT04(904-911).
IEEE DOI 0412
Combine sequence of 3-D data to generate deformable mesh models. BibRef

Cong, G.[Ge], Esser, M., Parvin, B., Bebis, G.N.,
Shape metamorphism using p-Laplacian equation,
ICPR04(IV: 15-18).
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Rangarajan, A.[Anand], Chui, H.[Haili], Mjolsness, E.[Eric],
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Liu, C.,
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Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Level Set Models for Volumes .