17.3 Optic Flow Computation and Use, Other Approaches

Yachida, M.[Masahiko],
Determining Velocity Maps by Spatio-Temporal Neighborhoods from Image Sequences,
CVGIP(21), No. 2, February 1983, pp. 262-279.
WWW Version. BibRef 8302
Earlier:
Determining Velocity Map by 3-D Iterative Estimation,
IJCAI81(716-718). BibRef

Zucker, S.W., Iverson, L.,
From Orientation Selection to Optical Flow,
CVGIP(37), No. 2, February 1987, pp. 196-220.
WWW Version. BibRef 8702
Earlier: A2, A1:
Orientation Selection to Optical Flow: A Computational Perspective,
CVWS87(184-189). BibRef

Iverson, L.,
Toward Discrete Geometric Models for Early Vision,
Ph.D.Thesis, June, 1994. McGill University. Relaxation. Texture flow. Postscript:
Postscript Version. or Tar file with separate chapters:
WWW Version. BibRef 9406

Lee, D.N.,
The Optical Flow Field: The Foundation of Vision,
Royal(B-290), 1980, pp. 169-179. BibRef 8000
And: No title available, but it is different. Perception(5), 1976, pp. 437-xx. BibRef

Labuz, J., Schalkoff, R.J.,
New Results Using an Integrated Model and Recursive Algorithm for Image Motion Estimation,
PRL(2), 1984, pp. 179-183. BibRef 8400

Schalkoff, R.J., Labuz, J.,
An Integrated Spatio-Temporal Model and Recursive Algorithm for Image Motion Estimation,
ICPR84(530-533). BibRef 8400

Aisbett, J.[Janet],
Optical Flow with an Intensity-Weighted Smoothing,
PAMI(11), No. 5, May 1989, pp. 512-522.
IEEE Abstract. IEEE Top Reference.
WWW Version. Gradient based approach with only the intensity gradient as a derivative. Performs better when images have NO strong texture. BibRef 8905

Driessen, J.N., Boroczky, L., Biemond, J.,
Pel-Recursive Motion Field Estimation from Image Sequences,
JVCIR(2), 1991, pp. 259-280. BibRef 9100

Fogel, S.V.,
The Estimation of Velocity Vector Fields from Time-Varying Image Sequences,
CVGIP(53), No. 3, May 1991, pp. 253-287.
WWW Version. BibRef 9105
And: Erratum: CVGIP(54), No. 3, November 1991, pp. 431-432.
WWW Version. BibRef
Earlier:
Implementation of a Nonlinear Approach to the Motion Correspondence Problem,
Motion89(87-98). Implementation issues for the earlier: BibRef
A Nonlinear Approach to the Motion Correspondence Problem,
ICCV88(619-628).
IEEE Abstract. IEEE Top Reference. Combining the optical flow constraints (relating image values) and directional smoothness constraints to get better estimates. There is a lot of derivation of the technique. BibRef

Shvaytser, H.[Haim],
Occam Algorithms for Computing Visual-Motion,
PAMI(17), No. 11, November 1995, pp. 1033-1042.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9511
Earlier: ICCV93(551-555).
IEEE DOI Link The best predictor is the simplest, defined in terms of encoding length. BibRef

Vaidya, V.G., Haralick, R.M.,
Wigner Distribution for 2D Motion Estimation from Noisy Images,
JVCIR(4), 1993, pp. 281-297. BibRef 9300

Huang, C.L., Chen, Y.T.,
Motion Estimation Method Using a 3D Steerable Filter,
IVC(13), No. 1, February 1995, pp. 21-32.
WWW Version. BibRef 9502

Chen, T.W.[Tsu Wang], and Lin, W.C.[Wei Chung], Chen, C.T.,
Artificial Neural Networks for 3-D Motion Analysis I: Rigid Motion,
TNN(6), No. 6, November 1995, pp. 1386-1393. BibRef 9511
And:
Artificial Neural Networks for 3-D Motion Analysis II: Nonrigid Motion,
TNN(6), No. 6, November 1995, pp. 1394-1401. See also Neural-Network Approach to CSG-Based 3-D Object Recognition, A. BibRef

Sayrol, E., Gasull, A., Fonollosa, J.R.,
Motion Estimation Using Higher-Order Statistics,
IP(5), No. 6, June 1996, pp. 1077-1084.
IEEE DOI Link 9607
BibRef

Anderson, J.M.M., Giannakis, G.B.,
Image Motion Estimation Algorithms Using Cumulants,
IP(4), No. 3, March 1995, pp. 346-357.
IEEE DOI Link BibRef 9503

Kirchner, H., Niemann, H.,
Finite Element Method for Determination of Optical Flow,
PRL(13), 1992, pp. 131-141. BibRef 9200

Strintzis, M.G., Kokkinidis, I.,
Maximum-Likelihood Motion Estimation in Ultrasound Image Sequences,
SPLetters(4), No. 6, June 1997, pp. 156-157.
IEEE Top Reference. 9706
BibRef

Rakshit, S., Anderson, C.H.,
Computation of Optical-Flow Using Basis Functions,
IP(6), No. 9, September 1997, pp. 1246-1254.
IEEE DOI Link 9709
BibRef

Spinei, A., Pellerin, D., Herault, J.,
Spatiotemporal Energy-Based Method for Velocity Estimation,
SP(65), No. 3, March 1998, pp. 347-362. 9806
BibRef

Vernon, D.[David],
Computation of instantaneous optical flow using the phase of Fourier components,
IVC(17), No. 3/4, March 1999, pp. 189-199.
WWW Version. BibRef 9903
Earlier:
Decoupling Fourier Components of Dynamic Image Sequences: A Theory of Signal Separation, Image Segmentation, and Optical Flow Estimation,
ECCV98(II: 69).
WWW Version. BibRef

Gray, W.S., Nabet, B.,
Volterra Series Analysis and Synthesis of a Neural Network for Velocity Estimation,
SMC-B(29), No. 2, April 1999, pp. 190. BibRef 9904

Li, H.D.[Hong-Dong], Liu, J.L.[Ji-Lin], Gu, W.[Weikang],
A new and fast approach for DPIV using an incompressible affine flow model,
MVA(11), No. 5, 2000, pp. 252-256.
HTML Version. 0004
BibRef

Yao, J.C.[Jian-Chao],
Estimation of 2D Displacement Field Based on Affine Geometric Invariance and Scene Constraints,
IJCV(46), No. 1, January 2002, pp. 25-50.
WWW Version. 0201
BibRef
Earlier:
Estimation of 2D Motion Field Based on Affine Geometric Invariance,
ICPR00(Vol III: 1037-1040).
IEEE DOI Link 0009
BibRef
Earlier:
Motion Blur Identification Based on Phase Change Experienced After Trial Restorations,
ICIP99(I:180-184).
IEEE Abstract. IEEE Top Reference. BibRef

Yao, J.C.[Jian-Chao],
Dynamic Vision in the Dynamic Scene: An Algebraic Approach,
ICARCV06(1-6).
IEEE DOI Link 0612
BibRef

Chen, L.F.[Li-Fen], Liao, H.Y.M.[Hong-Yuan Mark], Lin, J.C.[Ja-Chen],
Wavelet-based Optical Flow Estimation,
CirSysVideo(12), No. 1, January 2002, pp. 1-12.
IEEE Top Reference. 0202
BibRef
Earlier: A1, A3, A2: ICPR00(Vol III: 1056-1059).
IEEE DOI Link
IEEE DOI Link
HTML Version. 0009
BibRef

Foroosh, H.[Hassan], and Hoge, W.S.[W. Scott],
Motion Information in the Phase Domain,
VideoRegister03(Chapter 3). BibRef 0300

Barcelos, C.A.Z., Boaventura, M., Silva, Jr., E.C.,
A well-balanced flow equation for noise removal and edge detection,
IP(12), No. 7, July 2003, pp. 751-763.
IEEE DOI Link 0308
BibRef

Lai, S.H.[Shang-Hong],
Computation of optical flow under non-uniform brightness variations,
PRL(25), No. 8, June 2004, pp. 885-892.
WWW Version. 0405
BibRef

Teng, C.H.[Chin-Hung], Lai, S.H.[Shang-Hong], Chen, Y.S.[Yung-Sheng], Hsu, W.H.[Wen-Hsing],
Accurate optical flow computation under non-uniform brightness variations,
CVIU(97), No. 3, March 2005, pp. 315-346.
WWW Version. 0412
BibRef
Earlier:
Robust computation of optical flow under non-uniform illumination variations,
ICPR02(I: 327-330).
IEEE DOI Link 0211
BibRef

Condell, J.V.[Joan V.], Scotney, B.W.[Bryan W.], Morrow, P.J.[Philip J.],
Adaptive Grid Refinement Procedures for Efficient Optical Flow Computation,
IJCV(61), No. 1, January 2005, pp. 31-54.
WWW Version. 0410
BibRef
Earlier:
Evaluation of Uniform and Non-uniform Optical Flow Techniques Using Finite Element Methods,
DAGM03(116-123).
HTML Version. 0310
BibRef
Earlier:
Estimation of Motion through Inverse Finite Element Methods with Triangular Meshes,
CAIP01(333 ff.).
HTML Version. 0210
BibRef

Condell, J.V.[Joan V.], Scotney, B.W.[Bryan W.], Morrow, P.J.[Philip J.],
Adaptive vs. non-adaptive strategies for the computation of optical flow,
IJIST(16), No. 2, 2006, pp. 35-50.
WWW Version. 0703
BibRef
And:
The Effect of Presmoothing Image Sequences on the Computation of Optical Flow,
ICIAR06(I: 780-791).
Springer DOI Link 0610
BibRef

Foroosh, H.[Hassan],
Pixelwise-Adaptive Blind Optical Flow Assuming Nonstationary Statistics,
IP(14), No. 2, February 2005, pp. 222-230.
IEEE DOI Link 0501
BibRef
Earlier:
An adaptive scheme for estimating motion,
ICIP04(III: 1831-1834).
IEEE DOI Link 0505
BibRef

Foroosh, H.,
A Closed-form Solution for Optical Flow by Imposing Temporal Constraints,
ICIP01(III: 656-659).
IEEE Abstract. IEEE Top Reference. 0108
BibRef

Coimbra, M.T., Davies, M.,
Approximating Optical Flow Within the MPEG-2 Compressed Domain,
CirSysVideo(15), No. 1, January 2005, pp. 103-107.
IEEE Abstract. IEEE Top Reference. 0501
BibRef

Trucco, E., Tommasini, T., Roberto, V.,
Near-recursive optical flow from weighted image differences,
SMC-B(35), No. 1, February 2005, pp. 124-129.
IEEE Abstract. IEEE Top Reference. 0501
BibRef

Trucco, E., Viel, F., Roberto, V.,
Near-recursive optical flow from disturbance fields,
BMVC02(Poster Session). 0208
BibRef

Papenberg, N.[Nils], Bruhn, A.[Andrés], Brox, T.[Thomas], Didas, S.[Stephan], Weickert, J.[Joachim],
Highly Accurate Optic Flow Computation with Theoretically Justified Warping,
IJCV(67), No. 2, April 2006, pp. 141-158.
Springer DOI Link 0605
Grey value constancy, and gradient constancy, and the constancy of the Hessian and the Laplacian. BibRef

Brox, T.[Thomas], Bruhn, A.[Andrés], Papenberg, N.[Nils], Weickert, J.[Joachim],
High Accuracy Optical Flow Estimation Based on a Theory for Warping,
ECCV04(Vol IV: 25-36).
WWW Version. 0405
BibRef

Zimmer, H.[Henning], Bruhn, A.[Andrés], Weickert, J.[Joachim], Valgaerts, L.[Levi], Salgado, A.[Agustín], Rosenhahn, B.[Bodo], Seidel, H.P.[Hans-Peter],
Complementary Optic Flow,
EMMCVPR09(207-220).
Springer DOI Link 0908
BibRef

Brox, T.[Thomas], Rosenhahn, B.[Bodo], Cremers, D.[Daniel], Seidel, H.P.[Hans-Peter],
High Accuracy Optical Flow Serves 3-D Pose Tracking: Exploiting Contour and Flow Based Constraints,
ECCV06(II: 98-111).
Springer DOI Link 0608
BibRef

Rosenhahn, B.[Bodo], Brox, T.[Thomas], Cremers, D.[Daniel], Seidel, H.P.[Hans-Peter],
A Comparison of Shape Matching Methods for Contour Based Pose Estimation,
IWCIA06(263-276).
Springer DOI Link 0606
BibRef

Brox, T.[Thomas], Rosenhahn, B.[Bodo], Cremers, D.[Daniel], Seidel, H.P.[Hans-Peter],
Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking,
HUMO07(152-165).
Springer DOI Link 0710
BibRef

Brox, T.[Thomas], Rosenhahn, B.[Bodo], Kersting, U.G.[Uwe G.], Cremers, D.[Daniel],
Nonparametric Density Estimation for Human Pose Tracking,
DAGM06(546-555).
Springer DOI Link 0610
BibRef

Rosenhahn, B., Kersting, U.G., Smith, A.W., Gurney, J.K., Brox, T., Klette, R.,
A System for Marker-Less Human Motion Estimation,
DAGM05(230).
Springer DOI Link 0509
BibRef

Brox, T., Weickert, J.,
Nonlinear Matrix Diffusion for Optic Flow Estimation,
DAGM02(446 ff.).
HTML Version. 0303
BibRef

Gong, M.L.[Ming-Lun], Yang, Y.H.[Yee-Hong],
Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm,
IJCV(68), No. 3, July 2006, pp. 319-330.
Springer DOI Link 0606
BibRef
Earlier:
Estimate Large Motions Using Reliability-Based Dynamic Programming,
ICIP04(IV: 2559-2562).
IEEE DOI Link 0505
See also Real-Time Stereo Matching Using Orthogonal Reliability-Based Dynamic Programming. BibRef

Gong, M.L.[Ming-Lun],
Motion estimation using dynamic programming with selective path search,
ICPR04(IV: 203-206).
IEEE DOI Link 0409
BibRef

Makadia, A.[Ameesh], Daniilidis, K.[Kostas],
Rotation Recovery from Spherical Images without Correspondences,
PAMI(28), No. 7, July 2006, pp. 1170-1175.
IEEE DOI Link 0606
BibRef
Earlier:
Direct 3D-rotation estimation from spherical images via a generalized shift theorem,
CVPR03(II: 217-224).
IEEE Abstract. IEEE Top Reference. 0307
Mapping of omnidirectional image to sphere. Rotational camera motion analysis through generalized Fourier transform method. See also Correspondence-free Structure from Motion. BibRef

Daniilidis, K., Makadia, A., Bulow, T.,
Image processing in catadioptric planes: spatiotemporal derivatives and optical flow computation,
OMNIVIS02(3-10).
IEEE Abstract. IEEE Top Reference. 0310
BibRef

Makadia, A., Sorgi, L., Daniilidis, K.,
Rotation estimation from spherical images,
ICPR04(III: 590-593).
IEEE DOI Link 0409
See also Normalized Cross-Correlation for Spherical Images. BibRef

Tagliasacchi, M.[Marco],
A genetic algorithm for optical flow estimation,
IVC(25), No. 2, February 2007, pp. 141-147.
WWW Version. 0701
Optical flow; Genetic algorithms; Motion estimation BibRef

Lu, Z.Q.[Zong-Qing], Liao, Q.M.[Qing-Min], Pei, J.H.[Ji-Hong],
A Nonlinear Filtering Based Optical Flow Computation,
IJIG(9), No. 1, January 2009, pp. 121-132. 0903
BibRef

Lu, Z.Q.[Zong-Qing], Xie, W.X.[Wei-Xin],
A PDE-Based Method For Optical Flow Estimation,
ICPR06(II: 78-81).
WWW Version. 0609
BibRef

Aalaoui, E.M.I.[E.M. Ismaili], Ibn-Elhaj, E.[Elhassane], Bouyakhf, E.H.,
A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain,
JIVP(2009), No. 2009, pp. xx-yy.
WWW Version. 0903
Consider noise issues. BibRef

Abhau, J.[Jochen], Belhachmi, Z.[Zakaria], Scherzer, O.[Otmar],
On a Decomposition Model for Optical Flow,
EMMCVPR09(126-139).
Springer DOI Link 0908
BibRef

Schoueri, Y.[Yasmina], Scaccia, M.[Milena], Rekleitis, I.[Ioannis],
Optical Flow from Motion Blurred Color Images,
CRV09(1-7).
IEEE DOI Link 0905
BibRef

Rodríguez, A.L.[Antonio L.], López-de-Teruel, P.E.[Pedro E.], Ruiz, A.[Alberto],
Real-Time Descriptorless Feature Tracking,
CIAP09(853-862).
Springer DOI Link 0909
Long-term sparse optical flow. BibRef

Lin, D.[Dahua], Grimson, W.E.L.[W. Eric L.], Fisher, J.[John],
Learning visual flows: A Lie algebraic approach,
CVPR09(747-754).
IEEE DOI Link 0906
BibRef

Radgui, A.[Amina], Demonceaux, C.[Cédric], Rziza, M.[Mohammed], Mouaddib, E.M.[El Mustapha], Aboutajdine, D.[Driss],
An adapted Lucas-Kanade's method for optical flow estimation in catadioptric images,
OMNIVIS08(xx-yy). 0810
BibRef

Fehr, J.[Janis], Reisert, M.[Marco], Burkhardt, H.[Hans],
Fast and Accurate Rotation Estimation on the 2-Sphere without Correspondences,
ECCV08(II: 239-251).
Springer DOI Link 0810
BibRef

Kharbat, M., Aouf, N., Tsourdos, A., White, B.,
Robust Brightness Description for Computing Optical Flow,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Dellen, B., Woergoetter, F.,
A Local Algorithm for the Computation of Optic Flow via Constructive Interference of Global Fourier Components,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Glocker, B.[Ben], Paragios, N.[Nikos], Komodakis, N.[Nikos], Tziritas, G.[Georgios], Navab, N.[Nassir],
Optical flow estimation with uncertainties through dynamic MRFs,
CVPR08(1-8).
IEEE DOI Link 0806
BibRef

Feigin, M.[Micha], Sochen, N.A.[Nir A.], Vemuri, B.C.[Baba C.],
Efficient anisotropic alpha-Kernels decompositions and flows,
Tensor08(1-8).
IEEE DOI Link 0806
BibRef

Feigin, M.[Micha], Sochen, N.A.[Nir A.], Vemuri, B.C.[Baba C.],
Anisotropic alpha-Kernels and Associated Flows,
SSVM07(484-495).
Springer DOI Link 0705
Scale space computations. Fractional Laplacian. See also Scale Space and Edge Detection using Anisotropic Diffusion. BibRef

Fashandi, H.[Homa], Fazel-Rezai, R.[Reza], Pistorius, S.[Stephen],
Optical Flow and Total Least Squares Solution for Multi-scale Data in an Over-Determined System,
ISVC07(II: 33-42).
Springer DOI Link 0711
BibRef

Fahad, A.[Ahmed], Morris, T.[Tim],
Multiple Combined Constraints for Optical Flow Estimation,
ISVC07(II: 11-20).
Springer DOI Link 0711
BibRef

Faisal, M.[Mohammad], Barron, J.L.[John L.],
High Accuracy Optical Flow Method Based on a Theory for Warping: Implementation and Qualitative/Quantitative Evaluation,
ICIAR07(513-525).
Springer DOI Link 0708
BibRef

Dong, G.[Gang], Baskin, T.I., Palaniappan, K.,
Motion Flow Estimation from Image Sequences with Applications to Biological Growth and Motility,
ICIP06(1245-1248). 0610

IEEE DOI Link BibRef

Sun, Z.H.[Zhao-Hui],
A Three-Frame Approach to Constraint-Consistent Motion Estimation,
ICPR06(I: 35-38).
WWW Version. 0609
BibRef

Wang, H.Y.[Hai-Yun], Ma, K.K.[Kai-Kuang],
Accurate Optical Flow Estimation in Noisy Sequences by Robust Tensor-driven Anisotropic Diffusion,
ICIP05(III: 1292-1295).
IEEE DOI Link 0512
BibRef

Karantzalos, K., Paragios, N.,
Higher Order Polynomials, Free Form Deformations and Optical Flow Estimation,
ICIP05(III: 1280-1283).
IEEE DOI Link 0512
BibRef

Kim, J.[Jangheon], Sikora, T.,
Hybrid Recursive Energy-based Method for Robust Optical Flow on Large Motion Fields,
ICIP05(I: 129-132).
IEEE DOI Link 0512
BibRef

Willert, V., Schmuedderich, J., Eggert, J., Goerick, C., Koerner, E.,
Probabilistic Optical Flow Estimation for Large Pixel Displacements Utilizing Egomotion Flow Compensation,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Willert, V.[Volker], Eggert, J.[Julian], Clever, S.[Sebastian], Körner, E.[Edgar],
Probabilistic Color Optical Flow,
DAGM05(9).
Springer DOI Link 0509
BibRef

Hamid, R., Bobick, A., Yezzi, A.J.,
Audio-visual flow: A variational approach to multi-modal flow estimation,
ICIP04(IV: 2563-2566).
IEEE DOI Link 0505
BibRef

Stein, F.[Fridtjof],
Efficient Computation of Optical Flow Using the Census Transform,
DAGM04(79-86).
WWW Version. 0505
BibRef

Myerscough, P.J.,
Guiding Optical Flow Estimation,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Goncalves, N.[Nuno], Araujo, H.[Helder],
Linear solution for the pose estimation of noncentral catadioptric systems,
OMNIVIS07(1-7).
IEEE DOI Link 0710
BibRef
Earlier:
Projection model, 3D reconstruction and rigid motion estimation from non-central catadioptric images,
3DPVT04(325-332).
IEEE Abstract. IEEE Top Reference. 0412
BibRef
And:
Rigid motion estimation from non-central catadioptric images,
ICPR04(IV: 268-271).
IEEE DOI Link 0409
See also Fitting conics to paracatadioptric projections of lines. BibRef

Gupta, D., Daniilidis, K.,
Planar motion of a parabolic catadioptric camera,
ICPR04(IV: 68-71).
IEEE DOI Link 0409
BibRef

Ying, X.H.[Xiang-Hua], Hu, Z.Y.[Zhan-Yi],
Spherical objects based motion estimation for catadioptric cameras,
ICPR04(III: 231-234).
IEEE DOI Link 0409
BibRef

Eriksson, M., Carlsson, S.,
Maximizing validity in 2d motion analysis,
ICPR04(II: 179-183).
IEEE DOI Link 0409
BibRef

Stratmann, I.,
Omnidirectional imaging and optical flow,
OMNIVIS02(104-111).
IEEE Abstract. IEEE Top Reference. 0310
BibRef

Coquin, D., Bolon, P.,
A new method to compute the distortion vector field from two images,
ICPR02(I: 279-282).
IEEE DOI Link 0211
BibRef

Barron, J.L., Klette, R.,
Quantitative color optical flow,
ICPR02(IV: 251-255).
IEEE DOI Link 0211
BibRef

Auclair-Fortier, M.F., Poulin, P., Ziou, D., Allili, M.,
A computational algebraic topology approach for optical flow,
ICPR02(I: 352-355).
IEEE DOI Link 0211
BibRef

Makhervaks, V., Barequet, G., Bruckstein, A.M.,
Image flows and one-liner graphical image representation,
ICPR02(I: 640-643).
IEEE DOI Link 0211
BibRef

Lim, S., El Gamal, A.,
Optical Flow Estimation Using High Frame Rate Sequences,
ICIP01(II: 925-928).
IEEE Abstract. IEEE Top Reference. 0108
BibRef

Baumela, L., de Agapito, L., Bustos, P., Reid, I.D.,
Motion Estimation Using the Differential Epipolar Equation,
ICPR00(Vol III: 840-843).
IEEE DOI Link
HTML Version.
HTML Version. 0009
BibRef

Yao, J.,
Visual Motion Estimation Via Second Order Cone Programming,
ICIP00(Vol III: 604-607).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Chen, L.,
A Novel Affine Invariant Feature Set and Its Application in Motion Estimation,
ICIP00(Vol III: 612-615).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Roy, S.[Sebastien], Govindu, V.[Venu],
MRF Solutions for Probabilistic Optical Flow Formulations,
ICPR00(Vol III: 1041-1047).
IEEE DOI Link
HTML Version. 0009
BibRef

Qiu, M.L.[Mao-Lin],
Computing Optical Flow Based on the Mass-conserving Assumption,
ICPR00(Vol III: 1029-1032).
IEEE DOI Link
HTML Version. 0009
BibRef

Kristoffersen, E., Austvoll, I., Engan, K.,
Dense Motion Field Estimation Using Spatial Filtering and Quasi Eigenfunction Approximations,
ICIP05(III: 1268-1271).
IEEE DOI Link 0512
BibRef

Austvoll, I.,
Directional Filters and a New Structure for Estimation of Optical Flow,
ICIP00(Vol II: 574-577).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Clocksin, W.,
A New Method for Computing Optical Flow,
BMVC00(xx-yy).
PDF Version. 0009
BibRef

Socolinsky, D.A.[Diego A.], Wolff, L.B.[Lawrence B.],
Multispectral Optic Flow,
DARPA98(755-760). See also Multispectral image visualization through first-order fusion. BibRef 9800

Lundberg, A.J.[Andrew J.], Wolff, L.B.[Lawrence B.],
Optic Flow Estimation from 3D Wavelet Edge Detection,
DARPA97(375-378). BibRef 9700

Mester, R., Mühlich, M.,
Improving Motion and Orientation Estimation Using an Equilibrated Total Least Squares Approach,
ICIP01(II: 929-932).
IEEE Abstract. IEEE Top Reference. 0108
BibRef
Earlier: A2, A1:
The role of total least squares in motion analysis,
ECCV98(II: 305).
WWW Version. BibRef

Sporring, J.[Jon], and Nielsen, M.[Mads],
Direct estimation of First Order Optic Flow,
TAIA95(225-238). First order optic flow using Lie derivatives to make spatial filters where the flow is measured as Fourier phase shift. BibRef 9500

Kothari, R., and Bellando, J.,
Optical Flow Determination Using Topology Preserving Mappings,
ICIP97(III: 344-347).
IEEE DOI Link BibRef 9700

Giaccone, P.R., Greenhill, D.R., and Jones, G.A.,
Recovering Very Large Visual Motion Fields,
SCIA97(xx-yy) 9705

HTML Version. BibRef

Arnspang, J.,
Optic Acceleration,
ICCV88(364-373).
IEEE Abstract. IEEE Top Reference. BibRef 8800

Rougee, A., Levy, B.C., Willsky, A.S.,
Reconstruction of Two-Dimensional Velocity Fields as a Linear Estimation Problem,
ICCV87(646-650). BibRef 8700

Lai, J., Gauch, J., and Crisman, J.,
Using Color to Computer Optical Flow,
SPIE(2056), 1993, pp. 186-194. BibRef 9300

Cooper, D.H.[David H.], Madsen, B.R.[Bo René], Graham, J.[Jim],
Estimating Motion in Ultrasound Images of the Small Bowel: Optical Flow without Image Structure,
SCIA03(571-578).
WWW Version. 0310
BibRef

Cooper, D.H., and Graham, J.,
Estimating Motion in Noisy, Textured Images: Optical Flow in Medical Ultrasound,
BMVC96(Poster Session 2). 9608
University of Manchester BibRef

Lee, D., Papageorgiou, A., and Wasilkowski, G.W.,
Computing Optical Flow,
Motion89(99-106). BibRef 8900
Earlier:
Computational Aspects of Determining Optical Flow,
ICCV88(612-618).
IEEE Abstract. IEEE Top Reference. A study of some aspects (quote from abstract). BibRef

Blicher, A.P.[A. Peter], and Omohundro, S.M.[Stephen M.],
Unique Recovery of Motion and Optic Flow Via Lie Algebras,
IJCAI85(889-891). An abstract method that shows rigid 3D motion recovery is possible from the time derivative of smooth monochrome image at 6 points, or 2 points for color. BibRef 8500

Rodrigues, V., Castan, S., and Pailhes, L.M.,
Displacement Vector Field Computation by Temporal Covariance Model,
CVPR85(212-214). (Laboratoire CERFIA) Preliminary. BibRef 8500

Huang, L.Q., Aloimonos, Y.,
How Normal Flow Constrains Relative Depth for an Active Observer,
IVC(12), No. 7, September 1994, pp. 435-445.
WWW Version. BibRef 9409
Earlier:
Relative Depth from Motion Using Normal Flow: An Active and Purposive Solution,
Motion91(196-204). You can get relative information without computing optical flow. BibRef

Huang, L., Aloimonos, Y.,
The geometry of visual interception,
CVPR92(741-743).
IEEE Abstract. IEEE Top Reference. 0403
BibRef

Nelson, R.C., and Aloimonos, Y.,
Obstacle Avoidance Using Flow Field Divergence,
PAMI(11), No. 10, October 1989, pp. 1102-1106.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 8910
Earlier:
Using Flow Field Divergence for Obstacle Avoidance: Towards Qualitative Vision,
ICCV88(188-196).
IEEE Abstract. IEEE Top Reference. Flow field divergence is a clue to obstacles. Simple system. Terrible bibliography with many errors in it. BibRef

Nelson, R.C., and Aloimonos, Y.,
Finding Motion Parameters from Spherical Flow Fields (or the Advantages of Having Eyes in the Back of Your Head),
BioCyber(58), 1988, pp. 261-273. BibRef 8800
Earlier: CVWS87(145-150). If you have more information than is physically possible then you can solve some problems. BibRef

Gharavi, H., and Mills, M.,
Block Matching Motion Estimation Algorithms: New Results,
CirSys(37), No. 5, May 1990, pp. 649-651.
IEEE Top Reference. BibRef 9005

Magarey, J.[Julian], Kingsbury, N.G.[Nick G.],
Motion Estimation Using A Complex-Valued Wavelet Transform,
TSP(46), No. 4, April 1998, pp. 1069-1084. 9804
BibRef
Earlier:
An Improved Motion Estimation Algorithm Using Complex Wavelets,
ICIP96(I: 969-972).
IEEE DOI Link BibRef

Magarey, J.[Julian], Kokaram, A.[Anil], Kingsbury, N.[Nick],
Robust motion estimation using chrominance information in colour image sequences,
CIAP97(I: 486-493).
WWW Version. 9709
BibRef
And:
Optimal Schemes for Motion Estimation on Colour Image Sequences,
ICIP97(II: 187-190).
IEEE DOI Link 9710
BibRef

Young, R.W., Kingsbury, N.G.,
Frequency Domain Motion Estimation Using a Complex Lapped Transform,
IP(2), No. 1, January 1993, pp. 2-17.
IEEE DOI Link BibRef 9301

Efstratiadis, S.N., Katsaggelos, A.K.,
An Adaptive Regularized Recursive Displacement Estimation Algorithm,
IP(2), No. 3, July 1993, pp. 341-352.
IEEE DOI Link BibRef 9307

Zhang, J., Hanauer, G.G.,
The Application of Mean-Field Theory to Image Motion Estimation,
IP(4), No. 1, January 1995, pp. 19-33.
IEEE DOI Link BibRef 9501

Li, W., Salari, E.,
Successive Elimination Algorithm for Motion Estimation,
IP(4), No. 1, January 1995, pp. 105-107.
IEEE DOI Link BibRef 9501

Jong, C.M., Salari, E.,
Analysis of Image Deformation under Orthographic Projection and Flow Parameter Estimation,
PR(22), No. 3, 1989, pp. 309-315.
WWW Version. BibRef 8900

Nomura, A., Miike, H., Koga, K.,
Field Theory Approach for Determining Optical Flow,
PRL(12), 1991, pp. 183-190. BibRef 9100

Nomura, A., Miike, H., Koga, K.,
Determining Motion Fields Under Nonuniform Illumination,
PRL(16), No. 3, March 1995, pp. 285-296. BibRef 9503

Nomura, A.[Atsushi],
Spatio-temporal optimization method for determining motion vector fields under non-stationary illumination,
IVC(18), No. 12, September 2000, pp. 939-950.
WWW Version. 0008
BibRef
Earlier:
Integral based approach for determining motion vector fields,
CIAP97(I: 462-469).
WWW Version. 9709
BibRef

Cropper, S.J., Derrington, A.M.,
Detection and Motion Detection in Chromatic and Luminance Beats,
JOSA-A(13), No. 3, March 1996, pp. 401-407. BibRef 9603

Wang, R.Y.,
A Network Model for the Optic Flow Computation of the MST Neurons,
NeurNet(9), No. 3, April 1996, pp. 411-426. 9605
BibRef

Srinivasan, S.[Sridhar], Chellappa, R.[Rama],
Noise-resilient estimation of optical flow by use of overlapped basis functions,
JOSA-A(16), No. 3, March 1999, pp. 493-507. BibRef 9903
Earlier:
Optical Flow Using Overlapped Basis Functions for Solving Global Motion Problems,
ECCV98(II: 288).
WWW Version. BibRef
Earlier:
Robust Modeling and Estimation of Optical Flow with Overlapped Basis Functions,
UMDTR3721, December 1996.
WWW Version.
WWW Version. BibRef

Srinivasan, S., Chellappa, R.,
An Integrated Approach to Image Stabilization, Mosaicking and Super-Resolution,
DARPA97(247-254). BibRef 9700
And:
Image Stabilization and Mosaicking Using the Overlapped Basis Optical Flow Field,
ICIP97(III: 356-359).
IEEE DOI Link BibRef

Liu, H.C.[Hong-Che], Hong, T.H.[Tsai-Hong], Herman, M., Chellappa, R.,
A Generalized Motion Model for Estimating Optical Flow Using 3-D Hermite Polynomials,
ICPR94(A:361-366).
IEEE DOI Link BibRef 9400

Rekleitis, I.M.,
Optical flow recognition from the power spectrum of a single blurred image,
ICIP96(III: 791-794).
IEEE DOI Link 9610
BibRef

Davis, C.Q., Karu, Z.Z., Freeman, D.M.,
Equivalence of Subpixel Motion Estimators Based on Optical Flow and Block Matching,
SCV95(7-12) M.I.T. Rigid motions. Block matching: minimize the difference between shifted versions of the images. BibRef 9500

Vico, F.J., Garrido, F.J., Sandoval, F., Leibovic, N.,
A connectionist model for local speed estimation,
ICIP94(II: 262-266).
IEEE DOI Link 9411
BibRef

Amini, A.A.,
A Scalar Function Formulation For Optical Flow,
ECCV94(A:123-131).
Springer DOI Link BibRef 9400

Germain, F., Skordas, T.,
An Image Motion Estimation Technique Based on a Combined Statistical Test and Spatiotemporal Generalised Likelihood Ratio Approach,
ECCV94(A:152-157).
Springer DOI Link BibRef 9400

Cornelius, N.[Nancy], and Kanade, T.[Takeo],
Adapting Optical-Flow to Measure Object Motion in Reflectance and X-Ray Image Sequences,
Motion83(50-58). BibRef 8300
And: DARPA83(257-265). BibRef
And: CMU-CS-TR-83-119, CMU CS Dept. BibRef

Derou, D., Dinten, J.M., Herault, L., Niez, J.J.,
Physical-Model Based Reconstruction of the Global Instantaneous Velocity Field from Velocity Measurements at a Few Points,
PBMCV95(SESSION 3) BibRef 9500

Wang, W.H.[Wen-Hao], Lie, W.N.[Wen-Nung], Chen, Y.C.[Yung-Chang],
A fuzzy-computing method for rotation-invariant image tracking,
ICIP94(I: 540-544).
IEEE DOI Link 9411
BibRef

Sherman, I., Spitzer, H.,
Model for local image velocity detection of early visual processing,
ICPR94(A:819-821).
IEEE DOI Link 9410
BibRef

Boyce, J.F., Protheroe, S.R., Haddon, J.F.,
A relaxation computation of optic flow from spatial and temporal cooccurrence matrices,
ICPR92(III:594-597).
IEEE DOI Link 9208
BibRef

Markandey, V.[Vishal],
System and method for determining optical flow,
US_Patent5,680,487, Oct 21, 1997
WWW Version. BibRef 9710
And:
Optical flow computation for moving sensors,
US_Patent5,257,209, Oct 26, 1993
WWW Version. BibRef

Markandey, V., Flinchbaugh, B.E.,
Multispectral Constraints for Optical Flow Computation,
ICCV90(38-41).
IEEE DOI Link BibRef 9000

Werkhoven, P., Toet, A.,
The Estimation of Displacement Vector Fields by Means of Adaptive Affine Transformations,
ICPR86(798-800). BibRef 8600

Pieroni, G.G.,
Analyzing the Movement of a Wave Field by Computer,
ICPR86(903-906). BibRef 8600

Forbus, K.D.,
Spatial and Qualitative Aspects of Reasoning about Motion,
AAAI-80(170-173). BibRef 8000

Forbus, K.D.[Kenneth D.],
A Study of Qualitative and Geometric Knowledge in Reasoning about Motion,
MIT AI-TR-615, February 1981.
WWW Version. BibRef 8102

Lavin, M.A.,
Analysis of Scenes from a Moving Viewpoint,
MIT-AI79(183-208). BibRef 7900

Chapter on Optical Flow Field Computations and Use continues in
Error Analysis, Evaluation for Optical Flow .