Nagel, H.H.[Hans-Hellmut],
On a Constraint Equation for the
Estimation of Displacement Rates in Image Sequences,
PAMI(11), No. 1, January 1989, pp. 13-30.
IEEE DOI
BibRef
8901
Earlier:
Constraints for the Estimation of Displacement Vector Fields from
Image Sequences,
IJCAI83(945-951).
BibRef
And:
On the Estimation of Dense Displacement Vector Fields from
Image Sequences,
Motion83(59-65).
These are refinements of
See also Displacement Vectors Derived from Second-Order Intensity Variations in Image Sequences. paper with different assumptions about the data.
The paper addresses the problem of
See also Determining Optical Flow. for motion, smoothness constraint of
vector field of motion. Introduces an oriented smoothness
constraint. Derives a constraint equation from perspective
projection and differential geometry along with Lambertian
reflection properties and isotropic illumination.
BibRef
Nagel, H.H.,
On Change Detection and Displacement Vector Estimation in Image
Sequences,
PRL(1), no. 1, 1982, pp. 55-60.
BibRef
8200
Nagel, H.H.,
Optical-Flow Estimation and the Interaction Between Measurement Errors
at Adjacent Pixel Positions,
IJCV(15), No. 3, July 1995, pp. 271-288.
Springer DOI
Evaluation.
BibRef
9507
Nagel, H.H., and
Enkelmann, W.,
An Investigation of Smoothness Constraints for the Estimation of
Displacement Vector Fields from Image Sequences,
PAMI(8), No. 5, September 1986, pp. 565-593.
BibRef
8609
And:
Towards the Estimation of Displacement Vector Fields by
'Oriented Smoothness' Constraints,
ICPR84(6-8).
See also On a Constraint Equation for the Estimation of Displacement Rates in Image Sequences. Computes a lot of flow fields, maybe they can really be computed,
and shows the effects of different smoothness constraints.
BibRef
Nagel, H.H.,
Extending the 'Oriented Smoothness Constraint' into the Temporal
Domain and the Estimation of Derivatives of Optical Flow,
ECCV90(139-148).
Springer DOI Extension of the GVT paper given above.
BibRef
9000
Mitiche, A.,
Grisell, R., and
Aggarwal, J.K.,
On Smoothness of a Vector Field: Application to Optical Flow,
PAMI(10), No. 6, November 1988, pp. 943-949.
IEEE DOI
BibRef
8811
Kearney, J.K., and
Thompson, W.B.,
Bounding Constraint Propagation for Optical Flow Estimation,
MU88(1-21).
Proposes the use of confidence in the estimate to determine the
influence on neighbors for smoothing.
BibRef
8800
Simard, P.Y., and
Mailloux, G.E.,
A Projection Operator for the Restoration of
Divergence-Free Vector Fields,
PAMI(10), No. 2, March 1988, pp. 248-256.
IEEE DOI
BibRef
8803
Simard, P.Y.[Patrice Y.],
Mailloux, G.E.[Guy E.],
Vector Field Restoration by the Method of Convex Projections,
CVGIP(52), No. 3, December 1990, pp. 360-385.
Elsevier DOI Optical Flow field processing to get smooth consistent results.
BibRef
9012
Anandan, P., and
Weiss, R.[Richard],
A Confidence Measure and a Smoothness Constraint for the
Computation of Image Displacement Fields,
probably a UMass report of some sort, April 1987.
And:
Introducing a Smoothness Constraint in a Matching Approach
for the Computation of Optical Flow Fields,
CVWS85(186-194).
Change OFF in the title to Displacement Fields in
BibRef
8500
DARPA85(186-196).
Yet another criterion to apply in the computation process.
BibRef
Snyder, M.A.,
On the Mathematical Foundations of Smoothness Constraints
for the Determination of Optical Flow and for Surface Reconstruction,
PAMI(13), No. 11, November 1991, pp. 1105-1114.
IEEE DOI
BibRef
9111
Earlier:
Motion89(107-115).
BibRef
And:
DARPA89(1004-1011).
BibRef
And:
The Mathematical Foundations of Smoothness Constraints: A
New Class of Coupled Constraint,
DARPA90(154-161).
There are only 4 constraints possible and any constraint is a
linear combination of these 4.
BibRef
Haddadi, N.,
Kuo, C.C.J.,
Computation of Dense Optical Flow with a Parametric Smoothness Model,
JVCIR(4), 1993, pp. 309-323.
BibRef
9300
Chaudhury, K.,
Mehrotra, R.,
Optical-Flow Estimation Using Smoothness of
Intensity Trajectories,
CVGIP(60), No. 2, September 1994, pp. 230-244.
DOI Link Extended sequence. Use information in the extended sequence.
BibRef
9409
de Vleeschauwer, D.,
On the Smoothness Constraint in the Intensity-Based Estimation
of the Parallax Field,
MultiSP(6), No. 2, April 1995, pp. 113-135.
BibRef
9504
Wohn, K.[Kwangyoen],
Davis, L.S.[Larry S.],
Thrift, P.[Philip],
Motion Estimation Based on Multiple Local Constraints and
Nonlinear Smoothing,
PR(16), No. 6, 1983, pp. 563-570.
Elsevier DOI
9611
BibRef
Bartolini, F.,
Piva, A.,
Median Based Relaxation of Smoothness Constraints in
Optic Flow Computation,
PRL(18), No. 7, July 1997, pp. 649-655.
9711
BibRef
Alparone, L.,
Barni, M.,
Bartolini, F.,
Caldelli, R.,
Regularization of Optic Flow Estimates by Means of Weighted Vector
Median Filtering,
IP(8), No. 10, October 1999, pp. 1462-1467.
IEEE DOI
BibRef
9910
Bab-Hadiashar, A.[Alireza],
Suter, D.[David],
Robust Optic Flow Computation,
IJCV(29), No. 1, August 1998, pp. 59-77.
DOI Link
0010
BibRef
Earlier:
Optic Flow Calculation Using Robust Statistics,
CVPR97(988-993).
IEEE DOI
9704
BibRef
Earlier:
Robust Optic Flow Estimation Using Least Median of Squares,
ICIP96(I: 513-516).
IEEE DOI LMS in first stage only.
BibRef
Suter, D.,
Motion Estimation and Vector Splines,
CVPR94(939-942).
IEEE DOI Optical flow
BibRef
9400
Chen, F.[Fang],
Suter, D.[David],
Image Coordinate Transformation Based on DIV-CURL Vector Splines,
ICPR98(Vol I: 518-520).
IEEE DOI
9808
BibRef
Wang, H.Z.[Han-Zi],
Suter, D.,
Variable bandwidth QMDPE and its application in robust optical flow
estimation,
ICCV03(178-183).
IEEE DOI
0311
Robust estimator applied to optical flow.
BibRef
Weickert, J.[Joachim],
Schnörr, C.[Christoph],
Variational Optic Flow Computation with a Spatio-Temporal Smoothness
Constraint,
JMIV(14), No. 3, May 2001, pp. 245-255.
DOI Link
0106
BibRef
Ruhnau, P.[Paul],
Stahl, A.[Annette],
Schnörr, C.[Christoph],
On-Line Variational Estimation of Dynamical Fluid Flows with
Physics-Based Spatio-temporal Regularization,
DAGM06(444-454).
Springer DOI
0610
Award, GCPR.
BibRef
Weickert, J.[Joachim],
Schnörr, C.[Christoph],
A Theoretical Framework for Convex Regularizers in PDE-Based
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IJCV(45), No. 3, December 2001, pp. 245-264.
DOI Link
0111
Differential methods for optical flow.
See also Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization.
BibRef
Yuan, J.,
Schnorr, C.,
Kohlberger, T.,
Ruhnau, P.,
Convex set-based estimation of image flows,
ICPR04(I: 124-127).
IEEE DOI
0409
BibRef
Kohlberger, T.[Timo],
Schnörr, C.[Christoph],
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Domain Decomposition for Variational Optical-Flow Computation,
IP(14), No. 8, August 2005, pp. 1125-1137.
IEEE DOI
0508
BibRef
Earlier:
Parallel Variational Motion Estimation by Domain Decomposition and
Cluster Computing,
ECCV04(Vol IV: 205-216).
Springer DOI
0405
BibRef
Earlier:
Domain Decomposition for Parallel Variational Optical Flow Computation,
DAGM03(196-203).
Springer DOI
0310
See also Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization.
BibRef
Mileva, Y.[Yana],
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Illumination-Robust Variational Optical Flow with Photometric
Invariants,
DAGM07(152-162).
Springer DOI
0709
BibRef
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Feddern, C.[Christian],
Kohlberger, T.[Timo],
Schnörr, C.[Christoph],
Variational Optical Flow Computation in Real Time,
IP(14), No. 5, May 2005, pp. 608-615.
IEEE DOI
0505
BibRef
Earlier:
Real-Time Optic Flow Computation with Variational Methods,
CAIP03(222-229).
Springer DOI
0311
See also Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization.
BibRef
Mehl, L.[Lukas],
Beschle, C.[Cedric],
Barth, A.[Andrea],
Bruhn, A.[Andrés],
An Anisotropic Selection Scheme for Variational Optical Flow Methods
with Order-adaptive Regularisation,
SSVM21(140-152).
Springer DOI
2106
BibRef
Demetz, O.[Oliver],
Weickert, J.[Joachim],
Bruhn, A.[Andrés],
Welk, M.[Martin],
Beauty with Variational Methods:
An Optic Flow Approach to Hairstyle Simulation,
SSVM07(825-836).
Springer DOI
0705
BibRef
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Kohlberger, T.[Timo],
Schnörr, C.[Christoph],
A Multigrid Platform for Real-Time Motion Computation with
Discontinuity-Preserving Variational Methods,
IJCV(70), No. 3, December 2006, pp. 257-277.
Springer DOI
0608
BibRef
Earlier:
Discontinuity-Preserving Computation of Variational Optic Flow in
Real-Time,
ScaleSpace05(279-290).
Springer DOI
0505
BibRef
Gwosdek, P.[Pascal],
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Variational optic flow on the Sony PlayStation 3:
Accurate dense flow fields for real-time applications,
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WWW Link.
1011
BibRef
Scharr, H.[Hanno],
Spies, H.[Hagen],
Accurate optical flow in noisy image sequences using flow adapted
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SP:IC(20), No. 6, July 2005, pp. 537-553.
Elsevier DOI
0506
BibRef
Earlier: A2, A1:
Accurate Optical Flow in Noisy Image Sequences,
ICCV01(I: 587-592).
IEEE DOI
0106
3d anisotropic diffusion and motion estimation.
BibRef
Krajsek, K.[Kai],
Mester, R.[Rudolf],
Scharr, H.[Hanno],
Statistically Optimal Averaging for Image Restoration and Optical Flow
Estimation,
DAGM08(xx-yy).
Springer DOI
0806
Award, GCPR, HM.
BibRef
Nir, T.[Tal],
Bruckstein, A.M.[Alfred M.],
Kimmel, R.[Ron],
Over-Parameterized Variational Optical Flow,
IJCV(76), No. 2, February 2008, pp. 205-216.
Springer DOI
0801
BibRef
Rosman, G.[Guy],
Shem-Tov, S.[Shachar],
Bitton, D.[David],
Nir, T.[Tal],
Adiv, G.[Gilad],
Kimmel, R.[Ron],
Feuer, A.[Arie],
Bruckstein, A.M.[Alfred M.],
Over-Parameterized Optical Flow Using a Stereoscopic Constraint,
SSVM11(761-772).
Springer DOI
1201
BibRef
Doshi, A.[Ashish],
Bors, A.G.[Adrian G.],
Robust Processing of Optical Flow of Fluids,
IP(19), No. 9, September 2010, pp. 2332-2344.
IEEE DOI
1008
BibRef
Earlier:
Navier-Stokes formulation for modelling turbulent optical flow,
BMVC07(xx-yy).
PDF File.
0709
BibRef
Earlier:
Robust Diffusion of Structural Flows for Volumetric Image Interpolation,
ICIP06(1225-1228).
0610
IEEE DOI
BibRef
Earlier:
Optical Flow Diffusion with Robustified Kernels,
CAIP05(222).
Springer DOI
0509
BibRef
Doshi, A.[Ashish],
Bors, A.G.[Adrian G.],
Detecting Vorticity in Optical Flow of Fluids,
ICPR10(2118-2121).
IEEE DOI
1008
BibRef
Doshi, A.[Ashish],
Bors, A.G.[Adrian G.],
Smoothing of optical flow using robustified diffusion kernels,
IVC(28), No. 12, December 2010, pp. 1575-1589.
Elsevier DOI
1003
BibRef
Earlier:
Structural flow smoothing for shape interpolation,
ICPR06(III: 11-14).
IEEE DOI
0609
BibRef
Bhattacharyya, A.,
Mahajan, S.,
Fritz, M.,
Schiele, B.,
Roth, S.,
Normalizing Flows With Multi-Scale Autoregressive Priors,
CVPR20(8412-8421)
IEEE DOI
2008
Computational modeling, Couplings, Data models, Image generation,
Mars, Computational efficiency, Spatial resolution
BibRef
Yu, J.J.[Jason J.],
Harley, A.W.[Adam W.],
Derpanis, K.G.[Konstantinos G.],
Back to Basics: Unsupervised Learning of Optical Flow via Brightness
Constancy and Motion Smoothness,
MotionRep16(III: 3-10).
Springer DOI
1611
BibRef
Brosch, N.[Nicole],
Hosni, A.[Asmaa],
Rhemann, C.[Christoph],
Gelautz, M.[Margrit],
Spatio-Temporally Coherent Interactive Video Object Segmentation via
Efficient Filtering,
DAGM12(418-427).
Springer DOI
1209
BibRef
Hosni, A.[Asmaa],
Rhemann, C.[Christoph],
Bleyer, M.[Michael],
Gelautz, M.[Margrit],
Temporally Consistent Disparity and Optical Flow via Efficient
Spatio-temporal Filtering,
PSIVT11(I: 165-177).
Springer DOI
1111
BibRef
Zhao, J.[Jie],
Wang, Y.Q.[Yuan-Quan],
Wang, H.B.[Huai-Bin],
Optical Flow with Harmonic Constraint and Oriented Smoothness,
ICIG11(94-99).
IEEE DOI
1109
BibRef
Eibl, G.[Gunther],
Brandle, N.[Norbert],
Evaluation of clustering methods for finding dominant optical flow
fields in crowded scenes,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Okatani, T.[Takayuki],
A Probabilistic Approach to Linear Subspace Fitting for Computer Vision
Problems,
GenModel04(185).
IEEE DOI
0406
BibRef
Okatani, T.,
Deguchi, K.,
Toward a statistically optimal method for estimating geometric
relations from noisy data: cases of linear relations,
CVPR03(I: 432-439).
IEEE DOI
0307
optical flow estimation and affine structure and motion problems are
considered.
BibRef
Devlaminck, V.[Vincent],
Motion Estimation from Equation of Continuity. The Well-Conditioned
Computation Point of View,
ICIP99(III:700-703).
IEEE Abstract.
BibRef
9900
Herment, A.[Alain],
Giovannelli, J.F.,
Mousseaux, E.,
Idier, J.,
Decesare, A.,
Jolivet, O., and
Bittoun, J.,
Regularized Estimation of Flow Patterns in MR Velocimetry,
ICIP96(III: 291-294).
IEEE DOI
BibRef
9600
Wohn, K.[Kwangyoen],
Xie, H.C.[Hu-Chen],
Davis, L.S.[Larry S.], and
Rosenfeld, A.[Azriel],
Smoothing Optical Flow Fields,
DARPA83(61-63).
Guide the local smoothing of optic flow using global histograms,
a modified superspike for motion.
BibRef
8300
Chapter on Optical Flow Field Computations and Use continues in
Optical Flow Field -- Boundaries .