17.2.5 Large Displacement Optical Flow

Chapter Contents (Back)
Optical Flow. Large Displacement Flow.

Wu, Q.X.,
A Correlation-Relaxation-Labeling Framework for Computing Optical Flow: Template Matching from a New Perspective,
PAMI(17), No. 9, September 1995, pp. 843-853.
IEEE DOI Template Matching. Clouds. Low contrast, large displacements, and non-rigid motions. BibRef 9509

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 0606
BibRef
Earlier:
Estimate Large Motions Using Reliability-Based Dynamic Programming,
ICIP04(IV: 2559-2562).
IEEE DOI 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 0409
BibRef

Wills, J.[Josh], Agarwal, S.[Sameer], Belongie, S.J.[Serge J.],
A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion,
IJCV(68), No. 2, June 2006, pp. 125-143.
Springer DOI 0606
BibRef

Wills, J.[Josh], Belongie, S.J.[Serge J.],
A Feature-Based Approach for Determining Dense Long Range Correspondences,
ECCV04(Vol III: 170-182).
Springer DOI 0405
two stage process in which a planar model is used to get an approximation for the segmentation and the gross motion, and then a spline is used to refine the fit. BibRef

Alvarez, L.[Luis], Weickert, J.[Joachim], Sánchez, J.[Javier],
Reliable Estimation of Dense Optical Flow Fields with Large Displacements,
IJCV(39), No. 1, August 2000, pp. 41-56.
DOI Link 0008
BibRef
Earlier:
A Scale-Space Approach to Nonlocal Optical Flow Calculations,
ScaleSpace99(235-246). See also Dense Disparity Map Estimation Respecting Image Discontinuities: A PDE and Scale-Space Based Approach. Code: See also Robust Optical Flow Estimation. BibRef

Alvarez, L.[Luis], Deriche, R.[Rachid], Papadopoulo, T.[Théo], Sánchez, J.[Javier],
Symmetrical Dense Optical Flow Estimation with Occlusions Detection,
IJCV(75), No. 3, December 2007, pp. 371-385.
Springer DOI 0710
BibRef
Earlier: ECCV02(I: 721 ff.).
Springer DOI 0205
BibRef

Fransens, R.[Rik], Strecha, C.[Christoph], Van Gool, L.J.[Luc J.],
Optical flow based super-resolution: A probabilistic approach,
CVIU(106), No. 1, April 2007, pp. 106-115.
WWW Link. 0704
BibRef
Earlier:
Robust Estimation in the Presence of Spatially Coherent Outliers,
RANSAC06(102).
IEEE DOI 0609
BibRef
And:
A Mean Field EM-algorithm for Coherent Occlusion Handling in MAP-Estimation Prob,
CVPR06(I: 300-307).
IEEE DOI 0606
BibRef
Earlier:
A Probabilistic Approach to Optical Flow based Super-Resolution,
GenModel04(191).
IEEE DOI 0406
BibRef
Earlier: A2, A1, A3:
A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection,
SMVP04(71-82).
Springer DOI 0505
Super-resolution; Optical flow; Visibility computation; EM See also Combined Depth and Outlier Estimation in Multi-View Stereo. BibRef

Brox, T.[Thomas], Malik, J.[Jitendra],
Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation,
PAMI(33), No. 3, March 2011, pp. 500-513.
IEEE DOI 1102
Integrate correspondences from descriptor matching into a variational approach to gain the benefits of both. BibRef

Brox, T.[Thomas], Bregler, C.[Christoph], Malik, J.[Jitendra],
Large displacement optical flow,
CVPR09(41-48).
IEEE DOI 0906
BibRef

Bao, L.C.[Lin-Chao], Yang, Q.X.[Qing-Xiong], Jin, H.L.[Hai-Lin],
Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow,
IP(23), No. 12, December 2014, pp. 4996-5006.
IEEE DOI 1402
BibRef
Earlier: CVPR14(3534-3541)
IEEE DOI 1409
edge detection. Bilateral Filter BibRef

Revaud, J.[Jérôme], Weinzaepfel, P.[Philippe], Harchaoui, Z.[Zaid], Schmid, C.[Cordelia],
DeepMatching: Hierarchical Deformable Dense Matching,
IJCV(120), No. 3, December 2016, pp. 300-323.
Springer DOI 1609
BibRef
Earlier: A1, A2, A3, A4:
EpicFlow: Edge-preserving interpolation of correspondences for optical flow,
CVPR15(1164-1172)
IEEE DOI 1510
BibRef
Earlier: A2, A1, A3, A4:
DeepFlow: Large Displacement Optical Flow with Deep Matching,
ICCV13(1385-1392)
IEEE DOI 1403
deep convolutional networks BibRef

Palomares, R.P.[Roberto P.], Meinhardt-Llopis, E.[Enric], Ballester, C.[Coloma], Haro, G.[Gloria],
FALDOI: A New Minimization Strategy for Large Displacement Variational Optical Flow,
JMIV(58), No. 1, May 2017, pp. 27-46.
Springer DOI 1704
BibRef
Earlier: A1, A4, A3, Only:
A Rotation-Invariant Regularization Term for Optical Flow Related Problems,
ACCV14(V: 304-319).
Springer DOI 1504
BibRef

Ballester, C.[Coloma], Garrido, L.[Lluis], Lazcano, V.[Vanel], Caselles, V.[Vicent],
A TV-L1 Optical Flow Method with Occlusion Detection,
DAGM12(31-40).
Springer DOI 1209
BibRef


Fan, J.Z.[Jing-Zhe], Wang, Y.[Yan], Guo, L.[Lei],
A modified variational method for large displacement optical flow,
ICIVC17(128-132)
IEEE DOI 1708
Computer vision, Estimation, Image color analysis, Image motion analysis, Interpolation, Optical imaging, Robustness, descriptor matching, large displacement optical flow, variational, method BibRef

Munda, G.[Gottfried], Shekhovtsov, A.[Alexander], Knöbelreiter, P.[Patrick], Pock, T.[Thomas],
Scalable Full Flow with Learned Binary Descriptors,
GCPR17(321-332).
Springer DOI 1711
Large displacement optical flow. BibRef

Hu, Y., Li, Y., Song, R.,
Robust Interpolation of Correspondences for Large Displacement Optical Flow,
CVPR17(4791-4799)
IEEE DOI 1711
BibRef
Earlier: A1, A3, A2:
Efficient Coarse-to-Fine Patch Match for Large Displacement Optical Flow,
CVPR16(5704-5712)
IEEE DOI 1612
Adaptation models, Adaptive optics, Computational modeling, Estimation, Impedance matching, Interpolation, Robustness BibRef

Bailer, C., Taetz, B., Stricker, D.,
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation,
ICCV15(4015-4023)
IEEE DOI 1602
Adaptive optics BibRef

Verma, N.K., Gunesh, D.E., Rao, G.S.S.S., Mishra, A.,
High Accuracy Optical Flow Based Future Image Frame Predictor Model,
AIPR15(1-6)
IEEE DOI 1605
edge detection BibRef

Verma, N.K., Mishra, A.,
Large displacement optical flow based image predictor model,
AIPR14(1-7)
IEEE DOI 1504
edge detection BibRef

Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Sparse Flow: Sparse Matching for Small to Large Displacement Optical Flow,
WACV15(1100-1106)
IEEE DOI 1503
Computer vision BibRef

Le Coat, F.[Francois], Pissaloux, E.E.[Edwige E.],
Modelling the optical-flow with projective-transform approximation for large camera movements,
ICIP14(199-203)
IEEE DOI 1502
Biomedical optical imaging BibRef

Nie, Q.[Qiong], Bouchafa, S.[Samia], Merigot, A.[Alain],
Model-based optical flow for large displacements and homogeneous regions,
ICIP13(3865-3869)
IEEE DOI 1402
3D motion; block matching; c-velocity; egomotion; optical flow BibRef

Chang, H.S.[Haw-Shiuan], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Superpixel-based large displacement optical flow,
ICIP13(3835-3839)
IEEE DOI 1402
large displacement optical flow; mean shift; superpixel BibRef

Chen, Z.Y.[Zhuo-Yuan], Jin, H.L.[Hai-Lin], Lin, Z.[Zhe], Cohen, S.[Scott], Wu, Y.[Ying],
Large Displacement Optical Flow from Nearest Neighbor Fields,
CVPR13(2443-2450)
IEEE DOI 1309
Motion Segmentation; Optical Flow; PatchMatch; Randomized Algorithm BibRef

Ummenhofer, B.[Benjamin],
Large Displacement Optical Flow for Volumetric Image Sequences,
DAGM11(432-437).
Springer DOI 1109
BibRef

Willert, V.[Volker], Eggert, J.[Julian],
A stochastic dynamical system for optical flow estimation,
WDV09(711-718).
IEEE DOI 0910
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 File. 0809
BibRef

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

Agarwal, R., Sklansky, J.,
Estimating optical flow for large interframe displacements,
CAIP93(403-411).
Springer DOI 9309
BibRef

Agarwal, R., Sklansky, J.,
Estimating Optical Flow from Clustered Trajectories in Velocity-Time,
ICPR92(I:215-219).
IEEE DOI BibRef 9200

Chapter on Optical Flow Field Computations and Use continues in
Optical Flow for Simple Motions .


Last update:Dec 28, 2017 at 17:11:31