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Volumn 35, Issue 2, 2013, Pages 411-424

Object matching using a locally affine invariant and linear programming techniques

Author keywords

Feature matching; linear programming; locally affine invariant; object matching

Indexed keywords

AFFINE INVARIANT; AUXILIARY VARIABLES; FEATURE MATCHING; GEOMETRIC CONSTRAINT; GEOMETRIC RELATIONSHIPS; LEAST SQUARE; LINEAR PROGRAMMING FORMULATION; LINEAR PROGRAMMING TECHNIQUES; MATCHED POINTS; MATCHING ALGORITHM; MATCHING METHODS; MATCHING PROBLEMS; NEIGHBORING POINT; NON-RIGID OBJECTS; OBJECT MATCHING; OBJECTIVE FUNCTIONS; POINT SET;

EID: 84871758809     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.99     Document Type: Article
Times cited : (43)

References (44)
  • 1
    • 84871821276 scopus 로고    scopus 로고
    • lpsolve
    • lpsolve: sourceforge.net/projects/lpsolve, 2012.
    • (2012)
  • 2
    • 84871805453 scopus 로고    scopus 로고
    • Hotel
    • CMU
    • CMU "hotel" Data Set, http://vasc.ri.cmu.edu/idb/html/motion/ hotel/index.html, 2006.
    • (2006) Data Set
  • 3
    • 84871726850 scopus 로고    scopus 로고
    • House
    • CMU
    • CMU "house" Data Set, http://vasc.ri.cmu.edu/idb/html/motion/ house/index.html, 2006.
    • (2006) Data Set
  • 8
    • 1842426385 scopus 로고    scopus 로고
    • An eigenspace projection clustering method for inexact graph matching
    • Apr
    • T. Caelli and S. Kosinov, "An Eigenspace Projection Clustering Method for Inexact Graph Matching," IEEE Trans. Pattern Analayis and Machine Intelligence, vol. 26, no. 4, pp. 515-519, Apr. 2004.
    • (2004) IEEE Trans. Pattern Analayis and Machine Intelligence , vol.26 , Issue.4 , pp. 515-519
    • Caelli, T.1    Kosinov, S.2
  • 11
    • 0037209409 scopus 로고    scopus 로고
    • Spectral correspondence for point pattern matching
    • M. Carcassoni and E. Hancock, "Spectral Correspondence for Point Pattern Matching," Pattern Recognition, vol. 36, pp. 193-204, 2003.
    • (2003) Pattern Recognition , vol.36 , pp. 193-204
    • Carcassoni, M.1    Hancock, E.2
  • 13
    • 0042904903 scopus 로고    scopus 로고
    • A new point matching algorithm for non-rigid registration
    • H. Chui and A. Rangarajan, "A New Point Matching Algorithm for Non-Rigid Registration," Computer Vision and Image Understanding, vol. 89, pp. 114-141, 2003.
    • (2003) Computer Vision and Image Understanding , vol.89 , pp. 114-141
    • Chui, H.1    Rangarajan, A.2
  • 17
    • 0019574599 scopus 로고
    • Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
    • M.A. Fischler and R.C. Bolles, "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography," Comm. ACM, vol. 24, pp. 381-395, 1981.
    • (1981) Comm. ACM , vol.24 , pp. 381-395
    • Fischler, M.A.1    Bolles, R.C.2
  • 20
  • 23
    • 33745886518 scopus 로고    scopus 로고
    • A spectral technique for correspondence problems using pairwise constraints
    • M. Leordeanu and M. Hebert, "A Spectral Technique for Correspondence Problems Using Pairwise Constraints," Proc. IEEE Int'l Conf. Computer Vision, pp. 1482-1489, 2005.
    • (2005) Proc. IEEE Int'l Conf. Computer Vision , pp. 1482-1489
    • Leordeanu, M.1    Hebert, M.2
  • 25
    • 0028121950 scopus 로고
    • A markov random field model for object matching under contextual constraints
    • S.Z. Li, "A Markov Random Field Model for Object Matching Under Contextual Constraints," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 866-869, 1994.
    • (1994) Proc. IEEE Conf. Computer Vision and Pattern Recognition , pp. 866-869
    • Li, S.Z.1
  • 27
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l J. Computer Vision, vol. 60, pp. 91-110, 2004.
    • (2004) Int'l J. Computer Vision , vol.60 , pp. 91-110
    • Lowe, D.G.1
  • 29
    • 0032072467 scopus 로고    scopus 로고
    • A new algorithm for error-tolerant subgraph isomorphism detection
    • May
    • B.T. Messmer and H. Bunke, "A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 493-503, May 1998.
    • (1998) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.20 , Issue.5 , pp. 493-503
    • Messmer, B.T.1    Bunke, H.2
  • 30
    • 9644260534 scopus 로고    scopus 로고
    • Scale and affine invariant interest point detectors
    • K. Mikolajczyk and C. Schmid, "Scale and Affine Invariant Interest Point Detectors," Int'l J. Computer Vision, vol. 60, pp. 63-86, 2004.
    • (2004) Int'l J. Computer Vision , vol.60 , pp. 63-86
    • Mikolajczyk, K.1    Schmid, C.2
  • 31
    • 0033570815 scopus 로고    scopus 로고
    • Replicator equations, maximal cliques, and graph isomorphism
    • M. Pelillo, "Replicator Equations, Maximal Cliques, and Graph Isomorphism," Neural Computation, vol. 11, pp. 1933-1955, 1999.
    • (1999) Neural Computation , vol.11 , pp. 1933-1955
    • Pelillo, M.1
  • 32
    • 57149134890 scopus 로고    scopus 로고
    • A comparative analysis of ransac techniques leading to adaptive real-time random sample consensus
    • R. Raguram, J. Frahm, and M. Pollefeys, "A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus," Proc. European Conf. Computer Vision, vol. 2, pp. 500-513, 2008.
    • (2008) Proc. European Conf. Computer Vision , vol.2 , pp. 500-513
    • Raguram, R.1    Frahm, J.2    Pollefeys, M.3
  • 34
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • S. Roweis and L. Saul, "Nonlinear Dimensionality Reduction by Locally Linear Embedding," Science, vol. 290, no. 5500, pp. 2323-2326, 2000.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.1    Saul, L.2
  • 37
    • 34548752768 scopus 로고
    • Feature-based correspondence-an eigenvector approach
    • L. Shapiro and J. Brady, "Feature-Based Correspondence-An Eigenvector Approach," Image and Vision Computing, vol. 10, pp. 283-288, 1992.
    • (1992) Image and Vision Computing , vol.10 , pp. 283-288
    • Shapiro, L.1    Brady, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.