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Volumn 07-12-June-2015, Issue , 2015, Pages 1164-1172

EpicFlow: Edge-preserving interpolation of correspondences for optical flow

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; GEODESY; INTERPOLATION; MOTION ESTIMATION; OPTICAL FLOWS;

EID: 84959237250     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298720     Document Type: Conference Paper
Times cited : (841)

References (40)
  • 2
    • 0034245682 scopus 로고    scopus 로고
    • Reliable estimation of dense optical flow fields with large displacements
    • L. Alvarez, J. Weickert, and J. Sanchez. Reliable estimation of dense optical flow fields with large displacements. IJCV, 2000
    • (2000) IJCV
    • Alvarez, L.1    Weickert, J.2    Sanchez, J.3
  • 5
    • 84908235058 scopus 로고    scopus 로고
    • Fast edge-preserving patchmatch for large displacement optical flow
    • L. Bao, Q. Yang, and H. lin. Fast edge-preserving patchmatch for large displacement optical flow. IEEE Trans. Image Processing, 2014
    • (2014) IEEE Trans. Image Processing
    • Bao, L.1    Yang, Q.2    Lin, H.3
  • 7
    • 84898787668 scopus 로고    scopus 로고
    • A general dense image matching framework combining direct and feature-based costs
    • J. Braux-Zin, R. Dupont, and A. Bartoli. A general dense image matching framework combining direct and feature-based costs. In ICCV, 2013. 2, S
    • (2013) ICCV , pp. 2-S
    • Braux-Zin, J.1    Dupont, R.2    Bartoli, A.3
  • 8
    • 18844364899 scopus 로고    scopus 로고
    • High accuracy optical flow estimation based on a theory for warping
    • T. Brox, A. Bruhn, N. Papenberg, and J. Weickert. High accuracy optical flow estimation based on a theory for warping. In ECCV, 2004
    • (2004) ECCV
    • Brox, T.1    Bruhn, A.2    Papenberg, N.3    Weickert, J.4
  • 9
    • 79551562584 scopus 로고    scopus 로고
    • Large displacement optical flow: Descriptor matching in variational motion estimation
    • 1, 2, 7, S
    • T. Brox and J. Malik. Large displacement optical flow: descriptor matching in variational motion estimation. IEEE Trans. PAMI, 2011. 1, 2, 7, S
    • (2011) IEEE Trans. PAMI
    • Brox, T.1    Malik, J.2
  • 10
    • 84887338408 scopus 로고    scopus 로고
    • A naturalistic open source movie for optical flow evaluation
    • D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black. A naturalistic open source movie for optical flow evaluation. In ECCV, 2012. 1,2,5
    • (2012) ECCV , pp. 125
    • Butler, D.J.1    Wulff, J.2    Stanley, G.B.3    Black, M.J.4
  • 11
    • 85026933789 scopus 로고
    • A computational approach to edge detection
    • J. Canny. A computational approach to edge detection. IEEE Trans. PAMI, 19S6
    • (1956) IEEE Trans. PAMI
    • Canny, J.1
  • 12
    • 84887336889 scopus 로고    scopus 로고
    • Large displacement optical flow from nearest neighbor fields
    • Z. Chen, H. lin, Z. Lin, S. Cohen, and Y. Wu. Large displacement optical flow from nearest neighbor fields. In CVPR, 2013
    • (2013) CVPR
    • Chen, Z.1    Lin, H.2    Lin, Z.3    Cohen, S.4    Wu, Y.5
  • 14
    • 85044327992 scopus 로고    scopus 로고
    • Learning brightness transfer functions for the joint recovery of illumination changes and optical flow
    • O. Demetz, M. Stoll, S. Volz, J. Weickert, and A. Bruhn. Learning brightness transfer functions for the joint recovery of illumination changes and optical flow. In ECCV. 2014. S
    • (2014) ECCV , pp. 5
    • Demetz, O.1    Stoll, M.2    Volz, S.3    Weickert, J.4    Bruhn, A.5
  • 15
    • 84898820142 scopus 로고    scopus 로고
    • Structured forests for fast edge detection
    • P. Dollar and C. L. Zitnick. Structured forests for fast edge detection. In ICCV, 2013. 1,2,3,4,7
    • (2013) ICCV , pp. 12347
    • Dollar, P.1    Zitnick, C.L.2
  • 16
    • 84916927549 scopus 로고    scopus 로고
    • Vision meets robotics: T he KITTI dataset
    • A. Geiger, P. Lenz, C. Stiller, and R. Urtasun. Vision meets robotics: T he KITTI dataset. IJRR, 2013. 2,5
    • (2013) IJRR , pp. 2-5
    • Geiger, A.1    Lenz, P.2    Stiller, C.3    Urtasun, R.4
  • 18
    • 84866668394 scopus 로고    scopus 로고
    • Computing nearest-neighbor fields via propagation-assisted kd-trees
    • K. He and J. Sun. Computing nearest-neighbor fields via propagation-assisted kd-trees. In CVPR, 2012. 2,5
    • (2012) CVPR , pp. 2-5
    • He, K.1    Sun, J.2
  • 20
    • 84959236681 scopus 로고    scopus 로고
    • Optical flow with geometric occlusion estimation and fusion of mUltiple frames
    • R. Kennedy and C. J. Taylor. Optical flow with geometric occlusion estimation and fusion of mUltiple frames. In EMMCVPR, 2015. S
    • (2015) EMMCVPR , pp. 5
    • Kennedy, R.1    Taylor, C.J.2
  • 21
    • 84946817713 scopus 로고    scopus 로고
    • Geodesic object proposals
    • P. KrahenbUhl and V. Koltun. Geodesic object proposals. In ECCV. 2014
    • (2014) ECCV
    • KrahenbUhl, P.1    Koltun, V.2
  • 22
    • 84898778210 scopus 로고    scopus 로고
    • Locally affine sparse-to-dense matching for motion and occlusion estimation
    • M. Leordeanu, A. Zanfir, and C. Sminchisescu. Locally affine sparse-to-dense matching for motion and occlusion estimation. In ICCV, 2013. 1,2,4,7, S
    • (2013) ICCV , pp. 1247S
    • Leordeanu, M.1    Zanfir, A.2    Sminchisescu, C.3
  • 23
    • 84887322636 scopus 로고    scopus 로고
    • Patch match filter: Efficient edge-aware filtering meets randomized search for fast correspondence field estimation
    • J. Lu, H. Yang, D. Min, and M. Do. Patch match filter: Efficient edge-aware filtering meets randomized search for fast correspondence field estimation. In CVPR, 2013
    • (2013) CVPR
    • Lu, J.1    Yang, H.2    Min, D.3    Do, M.4
  • 24
    • 33646524955 scopus 로고    scopus 로고
    • Highly accurate optic flow computation with theoretically justified warping
    • N. Papenberg, A. Bruhn, T. Brox, S. Didas, and J. Weickert. Highly accurate optic flow computation with theoretically justified warping. !lCV, 2006
    • (2006) LCV
    • Papenberg, N.1    Bruhn, A.2    Brox, T.3    Didas, S.4    Weickert, J.5
  • 25
    • 84961190658 scopus 로고    scopus 로고
    • Non-local total generalized variation for optical flow estimation
    • R. Ranft), K. Bredies, and T. Pock. Non-local total generalized variation for optical flow estimation. In ECCV, 2014. S
    • (2014) ECCV , pp. 5
    • Ranft), R.1    Bredies, K.2    Pock, T.3
  • 26
    • 51949113705 scopus 로고    scopus 로고
    • Local grouping for optical flow
    • X. Ren. Local grouping for optical flow. In CVPR, 2008
    • (2005) CVPR
    • Ren, X.1
  • 27
    • 77953178803 scopus 로고    scopus 로고
    • Large displacement optical flow computation without warping
    • F. Steinbrucker, T. Pock, and D. Cremers. Large displacement optical flow computation without warping. In ICCV, 2009
    • (2009) ICCV
    • Steinbrucker, F.1    Pock, T.2    Cremers, D.3
  • 28
    • 85026929862 scopus 로고    scopus 로고
    • A quantitative analysis of current practices in optical flow estimation and the principles behind them
    • D. Sun, S. Roth, and M. J. Black. A quantitative analysis of current practices in optical flow estimation and the principles behind them. !lCV, 2014. 1,2, S
    • (2014) IlCV , pp. 12S
    • Sun, D.1    Roth, S.2    Black, M.J.3
  • 29
    • 85161961413 scopus 로고    scopus 로고
    • Layered image motion with explicit occlusions, temporal consistency, and depth ordering
    • D. Sun, E. B. Sudderth, and M. J. Black. Layered image motion with explicit occlusions, temporal consistency, and depth ordering. In NIPS, 2010
    • (2010) NIPS
    • Sun, D.1    Sudderth, E.B.2    Black, M.J.3
  • 30
    • 84925311322 scopus 로고    scopus 로고
    • An evaluation of data costs for optical flow
    • C. Vogel, S. Roth, and K. Schindler. An evaluation of data costs for optical flow. In GCPR, 2013. S
    • (2013) GCPR , pp. 5
    • Vogel, C.1    Roth, S.2    Schindler, K.3
  • 33
    • 77953209139 scopus 로고    scopus 로고
    • Structureand motion-adaptive regularization for high accuracy optic flow
    • A. Wedel, D. Cremers, T. Pock, and H. Bischof. Structureand motion-adaptive regularization for high accuracy optic flow. In ICCV, 2009
    • (2009) ICCV
    • Wedel, A.1    Cremers, D.2    Pock, T.3    Bischof, H.4
  • 34
    • 84898830536 scopus 로고    scopus 로고
    • Deepflow: Large displacement optical flow with deep matching
    • P. Weinzaepfel, J. Revaud, Z. Harchaoui, and C. Schmid. Deepflow: Large displacement optical flow with deep matching. In ICCV, 2013. 1,2,4,5,6,7, S
    • (2013) ICCV , pp. 124567S
    • Weinzaepfel, P.1    Revaud, J.2    Harchaoui, Z.3    Schmid, C.4
  • 37
    • 33646575547 scopus 로고    scopus 로고
    • A feature-based approach for dense segmentation and estimation of large disparity motion
    • J. Wills, S. Agarwal, and S. Belongie. A feature-based approach for dense segmentation and estimation of large disparity motion. IJCV, 2006
    • (2006) IJCV
    • Wills, J.1    Agarwal, S.2    Belongie, S.3
  • 38
    • 84865609390 scopus 로고    scopus 로고
    • Motion detail preserving optical flow estimation
    • L. Xu, J. lia, and Y. Matsushita. Motion detail preserving optical flow estimation. IEEE Trans. PAMI, 2012. 1,2,5, S
    • (2012) IEEE Trans. PAMI , pp. 125S
    • Xu, L.1    Lia, J.2    Matsushita, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.