17.5 Optical Flow Field -- Smoothness

Chapter Contents (Back)
Smoothness. Motion, Smoothness Constraint. Optical Flow, Smoothing.

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., and Mailloux, G.E.,
Vector Field Restoration by the Method of Convex Projections,
CVGIP(52), No. 3, December 1990, pp. 360-385.
WWW Link. 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.
WWW Link. 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

Whon, K., Davis, L.S., Thrift, P.,
Motion Estimation Based on Multiple Local Constraints and Nonlinear Smoothing,
PR(16), No. 6, 1983, pp. 563-570.
WWW Link. 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
BibRef

Weickert, J.[Joachim], Schnörr, C.[Christoph],
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion,
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

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,
RealTimeIP(5), No. 3, September 2010, pp. 163-177.
WWW Link. 1011
BibRef

Scharr, H.[Hanno], Spies, H.[Hagen],
Accurate optical flow in noisy image sequences using flow adapted anisotropic diffusion,
SP:IC(20), No. 6, July 2005, pp. 537-553.
WWW Link. 0506
BibRef
Earlier: A2, A1:
Accurate Optical Flow in Noisy Image Sequences,
ICCV01(I: 587-592).
IEEE DOI 0106
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
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


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 .


Last update:Mar 13, 2017 at 16:25:24