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Volumn 2017-October, Issue , 2017, Pages 2688-2696

Point Set Registration with Global-Local Correspondence and Transformation Estimation

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; GAUSSIAN DISTRIBUTION; MEDICAL IMAGING; REMOTE SENSING;

EID: 85041902293     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2017.291     Document Type: Conference Paper
Times cited : (40)

References (34)
  • 1
    • 0001640740 scopus 로고    scopus 로고
    • Robust and efficient estimation by minimising a density power divergence
    • A. Basu, I. Harris, N. Hjort, and M. Jones. Robust and efficient estimation by minimising a density power divergence. Biometrika, 85:549-559, 1998.
    • (1998) Biometrika , vol.85 , pp. 549-559
    • Basu, A.1    Harris, I.2    Hjort, N.3    Jones, M.4
  • 3
    • 79957563017 scopus 로고
    • Principal warps: Thin-plate splines and the decomposition of deformations
    • F. Bookstein. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Mach. Intell., 11:567-585, 1989.
    • (1989) IEEE Trans. Pattern Anal. Mach. Intell. , vol.11 , pp. 567-585
    • Bookstein, F.1
  • 4
    • 0033721293 scopus 로고    scopus 로고
    • A feature registration framework using mixture models
    • Hilton Head Island, SC
    • H. Chui and A. Rangarajan. A feature registration framework using mixture models. In Proc. IEEE MMBIA-2000, 190-197, Hilton Head Island, SC, 2000.
    • (2000) Proc. IEEE MMBIA-2000 , pp. 190-197
    • Chui, H.1    Rangarajan, A.2
  • 5
  • 6
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the em algorithm
    • A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the EM algorithm. J. R. Statist. Soc. Series B, 39:1-38, 1977.
    • (1977) J. R. Statist. Soc. Series B , vol.39 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 8
    • 79959497055 scopus 로고    scopus 로고
    • Robust point set registration using Gaussian mixture models
    • B. Jian and B. Vemuri. Robust point set registration using Gaussian mixture models. IEEE Trans. Pattern Anal. Mach. Intell., 33:1633-1645, 2011.
    • (2011) IEEE Trans. Pattern Anal. Mach. Intell. , vol.33 , pp. 1633-1645
    • Jian, B.1    Vemuri, B.2
  • 9
    • 0023173192 scopus 로고
    • A shortest augmenting path algorithm for dense and sparse linear assignment problems
    • R. Jonker and A. Volgenant. A shortest augmenting path algorithm for dense and sparse linear assignment problems. Computing, 38:325-340, 1987.
    • (1987) Computing , vol.38 , pp. 325-340
    • Jonker, R.1    Volgenant, A.2
  • 14
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis., 60:91-110, 2004.
    • (2004) Int. J. Comput. Vis. , vol.60 , pp. 91-110
    • Lowe, D.1
  • 15
    • 84922569289 scopus 로고    scopus 로고
    • Robust L2E estimation of transformation for non-rigid registration
    • J. Ma, W. Qiu, J. Zhao, Y. Ma, A. Yuille, and Z. Tu. Robust L2E estimation of transformation for non-rigid registration. IEEE Trans. Signal Proc., 63:1115-1129, 2015.
    • (2015) IEEE Trans. Signal Proc. , vol.63 , pp. 1115-1129
    • Ma, J.1    Qiu, W.2    Zhao, J.3    Ma, Y.4    Yuille, A.5    Tu, Z.6
  • 16
    • 84881032491 scopus 로고    scopus 로고
    • Regularized vector field learning with sparse approximation for mismatch removal
    • J. Ma, J. Zhao, J. Tian, X. Bai, and Z. Tu. Regularized vector field learning with sparse approximation for mismatch removal. Pattern Recognit., 46:3519-3532, 2013.
    • (2013) Pattern Recognit. , vol.46 , pp. 3519-3532
    • Ma, J.1    Zhao, J.2    Tian, J.3    Bai, X.4    Tu, Z.5
  • 18
    • 85003781887 scopus 로고    scopus 로고
    • Non-rigid point set registration by preserving global and local structures
    • J. Ma, J. Zhao, and A. Yuille. Non-rigid point set registration by preserving global and local structures. IEEE Trans. Image Process., 25:53-64, 2016.
    • (2016) IEEE Trans. Image Process. , vol.25 , pp. 53-64
    • Ma, J.1    Zhao, J.2    Yuille, A.3
  • 23
    • 0002788893 scopus 로고    scopus 로고
    • A view of the em algorithm that justifies incremental, sparse, and other variants
    • Springer Netherlands, Dordrecht
    • M. Neal, Radford and G. Hinton. A view of the EM algorithm that justifies incremental, sparse, and other variants. Learning in Graphical Models, 355-368. Springer Netherlands, Dordrecht, 1998.
    • (1998) Learning in Graphical Models , pp. 355-368
    • Neal, M.1    Radford2    Hinton, G.3
  • 25
    • 84959423047 scopus 로고    scopus 로고
    • Robust cpd algorithm for non-rigid point set registration based on structure information
    • L. Peng, G. Li, M. Xiao, and L. Xie. Robust cpd algorithm for non-rigid point set registration based on structure information. PLoS ONE, 11 (2):e0148483, 2016.
    • (2016) PLoS ONE , vol.11 , Issue.2 , pp. e0148483
    • Peng, L.1    Li, G.2    Xiao, M.3    Xie, L.4
  • 28
    • 0035419755 scopus 로고    scopus 로고
    • Parametric statistical modeling by minimum integrated sqaure error
    • D. Scott. Parametric statistical modeling by minimum integrated sqaure error. Technometrics, 43:274-285, 2001.
    • (2001) Technometrics , vol.43 , pp. 274-285
    • Scott, D.1
  • 29
    • 0003241883 scopus 로고
    • Spline models for observational data
    • Philadelphia, Pennsylvania
    • G. Wahba. Spline models for observational data. SIAM, Philadelphia, Pennsylvania, 1990.
    • (1990) SIAM
    • Wahba, G.1
  • 30
    • 84948571400 scopus 로고    scopus 로고
    • A robust non-rigid point set registration method based on asymmetric Gaussian representation
    • G. Wang, Z. Wang, Y. Chen, andW. Zhao. A robust non-rigid point set registration method based on asymmetric Gaussian representation. Comput. Vis. Image Understand., 141:67-80, 2015.
    • (2015) Comput. Vis. Image Understand. , vol.141 , pp. 67-80
    • Wang, G.1    Wang, Z.2    Chen, Y.3    Zhao, W.4
  • 31
    • 84927135165 scopus 로고    scopus 로고
    • Robust point matching method for multimodal retinal image registration
    • G. Wang, Z. Wang, Y. Chen, and W. Zhao. Robust point matching method for multimodal retinal image registration. Biomed. Signal Process. Control, 19:68-76, 2015.
    • (2015) Biomed. Signal Process. Control , vol.19 , pp. 68-76
    • Wang, G.1    Wang, Z.2    Chen, Y.3    Zhao, W.4
  • 32
    • 84908049634 scopus 로고    scopus 로고
    • A robust global and local mixture distance based non-rigid point set registration
    • Y. Yang, S. Ong, and K. Foong. A robust global and local mixture distance based non-rigid point set registration. Pattern Recognit., 48:156-173, 2015.
    • (2015) Pattern Recognit. , vol.48 , pp. 156-173
    • Yang, Y.1    Ong, S.2    Foong, K.3
  • 33
    • 0000860704 scopus 로고
    • A mathematical analysis of the motion coherence theory
    • A. Yuille and N. Grzywacz. A mathematical analysis of the motion coherence theory. Int. J. Comput. Vis., 3:155-175, 1989.
    • (1989) Int. J. Comput. Vis. , vol.3 , pp. 155-175
    • Yuille, A.1    Grzywacz, N.2
  • 34
    • 33144483552 scopus 로고    scopus 로고
    • Robust point matching for nonrigid shapes by preserving local neighborhood structures
    • Y. Zheng and D. Doermann. Robust point matching for nonrigid shapes by preserving local neighborhood structures. IEEE Trans. Pattern Anal. Mach. Intell., 28:643-649, 2006.
    • (2006) IEEE Trans. Pattern Anal. Mach. Intell. , vol.28 , pp. 643-649
    • Zheng, Y.1    Doermann, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.