메뉴 건너뛰기




Volumn 25, Issue 4, 2014, Pages 971-983

When standard RANSAC is not enough: Cross-media visual matching with hypothesis relevancy

Author keywords

3D viewpoint estimation; Image registration; Object detection; Shape matching

Indexed keywords

COMPUTER GRAPHICS; IMAGE REGISTRATION;

EID: 84899955793     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-013-0571-4     Document Type: Article
Times cited : (20)

References (51)
  • 1
    • 84879691332 scopus 로고    scopus 로고
    • Robust and accurate pattern matching in fuzzy space for fiducial mark alignment
    • Cui, X.; Kim, H.; Park, E.; Choi, H.: Robust and accurate pattern matching in fuzzy space for fiducial mark alignment. MVA 24(3), 447-459 (2012)
    • (2012) MVA , vol.24 , Issue.3 , pp. 447-459
    • Cui, X.1    Kim, H.2    Park, E.3    Choi, H.4
  • 2
    • 78650971208 scopus 로고    scopus 로고
    • Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours
    • ACM, New York
    • Yoon, S.; Scherer, M.; Schreck, T.; Kuijper, A.: Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours. In: ACM-MM, pp. 193-200. ACM, New York (2010)
    • (2010) ACM-MM , pp. 193-200
    • Yoon, S.1    Scherer, M.2    Schreck, T.3    Kuijper, A.4
  • 3
    • 0019574599 scopus 로고
    • Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography
    • Fischler, M.; Bolles, R.: Random sample consensus: a paradigm for model fitting with application to image analysis and automated cartography. Com. ACM 24, 381-395 (1981)
    • (1981) Com. ACM , vol.24 , pp. 381-395
    • Fischler, M.1    Bolles, R.2
  • 5
    • 84898917134 scopus 로고    scopus 로고
    • Performance evaluation of RANSAC family
    • Choi, S.; Kim, T.; Yu, W.: Performance evaluation of RANSAC family. In: BMVC, pp. 1-12 (2009)
    • (2009) BMVC , pp. 1-12
    • Choi, S.1    Kim, T.2    Yu, W.3
  • 6
    • 84898435987 scopus 로고    scopus 로고
    • An effective bail-out test for RANSAC consensus scoring
    • Capel, D.: An effective bail-out test for RANSAC consensus scoring. In: BMVC, pp. 629-638 (2005)
    • (2005) BMVC , pp. 629-638
    • Capel, D.1
  • 7
    • 24644499558 scopus 로고    scopus 로고
    • Matching with PROSAC-progressive sample consensus
    • Chum, O.; Matas, J.: Matching with PROSAC-progressive sample consensus. In: CVPR, vol. 1, pp. 220-226 (2005)
    • (2005) CVPR , vol.1 , pp. 220-226
    • Chum, O.1    Matas, J.2
  • 8
    • 33745902531 scopus 로고    scopus 로고
    • Randomized RANSAC with sequential probability ratio test
    • IEEE, New York
    • Matas, J.; Chum, O.: Randomized RANSAC with sequential probability ratio test. In: ICCV,vol. 2, pp. 1727-1732. IEEE, New York (2005)
    • (2005) ICCV , vol.2 , pp. 1727-1732
    • Matas, J.1    Chum, O.2
  • 9
    • 84863171112 scopus 로고    scopus 로고
    • Accelerated hypothesis generation for multi-structure data via preference analysis
    • Chin, T.; Yu, J.; Suter, D.: Accelerated hypothesis generation for multi-structure data via preference analysis. IEEE Trans. Pattern Anal. Mach. Intell. 34, 625-638 (2012)
    • (2012) IEEE Trans. Pattern Anal. Mach. Intell , vol.34 , pp. 625-638
    • Chin, T.1    Yu, J.2    Suter, D.3
  • 10
    • 77953201614 scopus 로고    scopus 로고
    • SCRAMSAC: Improving RANSAC's efficiency with a spatial consistency filter
    • IEEE, New York
    • Sattler, T.; Leibe, B.; Kobbelt, L.: SCRAMSAC: improving RANSAC's efficiency with a spatial consistency filter. In: ICCV, pp. 2090-2097. IEEE, New York (2009)
    • (2009) ICCV , pp. 2090-2097
    • Sattler, T.1    Leibe, B.2    Kobbelt, L.3
  • 12
    • 57149134890 scopus 로고    scopus 로고
    • A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus
    • Raguram, R.; Frahm, J.; Pollefeys, M.: A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus. In: ECCV, pp. 500-513. (2008)
    • (2008) ECCV , pp. 500-513
    • Raguram, R.1    Frahm, J.2    Pollefeys, M.3
  • 13
    • 80051638475 scopus 로고    scopus 로고
    • Performance evaluation of 1-point-RANSAC visual odometry
    • Scaramuzza, D.: Performance evaluation of 1-point-RANSAC visual odometry. JFR 28, 792-811 (2011)
    • (2011) JFR , vol.28 , pp. 792-811
    • Scaramuzza, D.1
  • 14
    • 33845590625 scopus 로고    scopus 로고
    • RANSAC for (quasi-) degenerate data (QDEGSAC)
    • IEEE, New York
    • Frahm, J.; Pollefeys, M.: RANSAC for (quasi-) degenerate data (QDEGSAC). In: CVPR, vol. 1, pp. 453-460. IEEE, New York (2006)
    • (2006) CVPR , vol.1 , pp. 453-460
    • Frahm, J.1    Pollefeys, M.2
  • 15
    • 0033894631 scopus 로고    scopus 로고
    • MLESAC: A new robust estimator with application to estimating image geometry
    • Torr, P.; Zisserman, A.: MLESAC: a new robust estimator with application to estimating image geometry. CVIU 78, 138-156 (2000)
    • (2000) CVIU , vol.78 , pp. 138-156
    • Torr, P.1    Zisserman, A.2
  • 16
    • 84867889794 scopus 로고    scopus 로고
    • In defence of RANSAC for outlier rejection in deformable registration
    • Tran, Q.H.; Chin, T.J.; Carneiro, G.; Brown, M.; Suter, D.: In defence of RANSAC for outlier rejection in deformable registration. In: ECCV, pp. 274-287 (2012)
    • (2012) ECCV , pp. 274-287
    • Tran Q., .H.1    Chin T., .J.2    Carneiro, G.3    Brown, M.4    Suter, D.5
  • 17
    • 84868116768 scopus 로고    scopus 로고
    • A robust homography estimation method based on keypoint consensus and appearance similarity
    • IEEE, New York
    • Yan, Q.; Xu, Y.; Yang, X.: A robust homography estimation method based on keypoint consensus and appearance similarity. In: ICME, pp. 586-591. IEEE, New York (2012)
    • (2012) ICME , pp. 586-591
    • Yan, Q.1    Xu, Y.2    Yang, X.3
  • 18
    • 77957932934 scopus 로고    scopus 로고
    • RANSAC-SVM for large-scale datasets
    • IEEE, New York
    • Nishida, K.; Kurita, T.: RANSAC-SVM for large-scale datasets. In: ICPR, pp. 1-4. IEEE, New York (2008)
    • (2008) ICPR , pp. 1-4
    • Nishida, K.1    Kurita, T.2
  • 20
    • 80052816878 scopus 로고    scopus 로고
    • Multiple random subset-kernel learning
    • Springer, Berlin
    • Nishida, K.; Fujiki, J.; Kurita, T.: Multiple random subset-kernel learning. In: CAIP, pp. 343-350. Springer, Berlin (2011)
    • (2011) CAIP , pp. 343-350
    • Nishida, K.1    Fujiki, J.2    Kurita, T.3
  • 21
    • 33745826320 scopus 로고    scopus 로고
    • Aligning sequences and actions by maximizing space-time correlations
    • Ukrainitz, Y.; Irani, M.: Aligning sequences and actions by maximizing space-time correlations. In: ECCV, pp. 538-550 (2006)
    • (2006) ECCV , pp. 538-550
    • Ukrainitz, Y.1    Irani, M.2
  • 22
  • 24
    • 27644547620 scopus 로고    scopus 로고
    • A performance evaluation of local descriptors
    • 10.1109/TPAMI.2005.188
    • Mikolajczyk, K.; Schmid, C.: A performance evaluation of local descriptors. TPAMI 27, 1615-1630 (2005)
    • (2005) TPAMI , vol.27 , pp. 1615-1630
    • Mikolajczyk, K.1    Schmid, C.2
  • 25
    • 77953225581 scopus 로고    scopus 로고
    • Constructing implicit 3D shape models for pose estimation
    • Arie-Nachimson, M.; Basri, R.: Constructing implicit 3D shape models for pose estimation. In: ICCV, pp. 1341-1348 (2009)
    • (2009) ICCV , pp. 1341-1348
    • Arie-Nachimson, M.1    Basri, R.2
  • 26
    • 84856656486 scopus 로고    scopus 로고
    • Viewpoint-aware object detection and pose estimation
    • IEEE, New York
    • Glasner, D.; Galun, M.; Alpert, S.; Basri, R.; Shakhnarovich, G.: Viewpoint-aware object detection and pose estimation. In: ICCV, pp. 1275-1282. IEEE, New York (2011)
    • (2011) ICCV , pp. 1275-1282
    • Glasner, D.1    Galun, M.2    Alpert, S.3    Basri, R.4    Shakhnarovich, G.5
  • 27
    • 77953177125 scopus 로고    scopus 로고
    • Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories
    • IEEE, New York
    • Su, H.; Sun, M.; Fei-Fei, L.; Savarese, S.: Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories. In: ICCV, pp. 213-220. IEEE, New York (2009)
    • (2009) ICCV , pp. 213-220
    • Su, H.1    Sun, M.2    Fei-Fei, L.3    Savarese, S.4
  • 28
    • 84898901720 scopus 로고    scopus 로고
    • PWP3D: Real-time segmentation and tracking of 3D objects
    • Prisacariu, V.; Reid, I.: PWP3D: Real-time segmentation and tracking of 3D objects. In: BMVC. (2009)
    • (2009) BMVC
    • Prisacariu, V.1    Reid, I.2
  • 29
    • 70450178442 scopus 로고    scopus 로고
    • Non-rigid 2D-3D pose estimation and 2D image segmentation
    • Sandhu, R.; Dambreville, S.; Yezzi, A.; Tannenbaum, A.: Non-rigid 2D-3D pose estimation and 2D image segmentation. In: CVPR, pp. 786-793 (2009)
    • (2009) CVPR , pp. 786-793
    • Sandhu, R.1    Dambreville, S.2    Yezzi, A.3    Tannenbaum, A.4
  • 30
    • 51949111368 scopus 로고    scopus 로고
    • 3D model matching with viewpoint-invariant patches (VIP)
    • Wu, C.; Clipp, B.; Li, X.; Frahm, J.; Pollefeys, M.: 3D model matching with viewpoint-invariant patches (VIP). In: CVPR, pp. 1-8 (2008)
    • (2008) CVPR , pp. 1-8
    • Wu, C.1    Clipp, B.2    Li, X.3    Frahm, J.4    Pollefeys, M.5
  • 34
    • 84898770404 scopus 로고    scopus 로고
    • Viewing real-world faces in 3D
    • Hassner, T.: Viewing real-world faces in 3D. In: ICCV (2013)
    • (2013) ICCV
    • Hassner, T.1
  • 35
    • 84898454739 scopus 로고    scopus 로고
    • Back to the future: Learning shape models from 3D CAD data
    • Stark, M.; Goesele, M.; Schiele, B.: Back to the future: learning shape models from 3D CAD data. In: BMVC, pp. 106.1-106.11 (2010)
    • (2010) BMVC , pp. 1061-10611
    • Stark, M.1    Goesele, M.2    Schiele, B.3
  • 36
    • 77955993906 scopus 로고    scopus 로고
    • Multi-view object class detection with a 3D geometric model
    • Liebelt, J.; Schmid, C.: Multi-view object class detection with a 3D geometric model. In: CVPR, pp. 1688-1695 (2010)
    • (2010) CVPR , pp. 1688-1695
    • Liebelt, J.1    Schmid, C.2
  • 37
    • 51949095797 scopus 로고    scopus 로고
    • Viewpoint-independent object class detection using 3D feature maps
    • Liebelt, J.; Schmid, C.; Schertler, K.: Viewpoint-independent object class detection using 3D feature maps. In: CVPR, pp. 1-8 (2008)
    • (2008) CVPR , pp. 1-8
    • Liebelt, J.1    Schmid, C.2    Schertler, K.3
  • 39
    • 28444493739 scopus 로고    scopus 로고
    • Combining probability from independent tests: The weighted z -method is superior to Fisher's approach
    • 10.1111/j.1420-9101.2005.00917.x
    • Whitlock, M.: Combining probability from independent tests: the weighted z -method is superior to Fisher's approach. J. Evol. Biol. 18, 1368-1373 (2005)
    • (2005) J. Evol. Biol. , vol.18 , pp. 1368-1373
    • Whitlock, M.1
  • 40
    • 0031185845 scopus 로고    scopus 로고
    • Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection
    • 10.1109/34.598228
    • Belhumeur, P.; Hespanha, J.; Kriegman, D.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. TPAMI 19, 711-720 (1997)
    • (1997) TPAMI , vol.19 , pp. 711-720
    • Belhumeur, P.1    Hespanha, J.2    Kriegman, D.3
  • 41
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • 10.1023/B:VISI.0000029664.99615.94
    • Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV 60, 91-110 (2004)
    • (2004) IJCV , vol.60 , pp. 91-110
    • Lowe, D.1
  • 42
    • 9644260534 scopus 로고    scopus 로고
    • Scale and affine invariant interest point detectors
    • Mikolajcyk, K.; Schmid, C.: Scale and affine invariant interest point detectors. IJCV 60, 63-86 (2004). http://www.robots.ox.ac.uk/~vgg/research/ affine/
    • (2004) IJCV , vol.60 , pp. 63-86
    • Mikolajcyk, K.1    Schmid, C.2
  • 43
    • 84866670262 scopus 로고    scopus 로고
    • On sifts and their scales
    • IEEE, New York
    • Hassner, T.; Mayzels, V.; Zelnik-Manor, L.: On sifts and their scales. In: CVPR, pp. 1522-1528. IEEE, New York (2012)
    • (2012) CVPR , pp. 1522-1528
    • Hassner, T.1    Mayzels, V.2    Zelnik-Manor, L.3
  • 45
    • 84872359384 scopus 로고    scopus 로고
    • Car model recognition by utilizing symmetric property to overcome severe pose variation
    • Gu, H.Z.; Lee, S.Y.: Car model recognition by utilizing symmetric property to overcome severe pose variation. MVA 24(2), 255-274 (2012)
    • (2012) MVA , vol.24 , Issue.2 , pp. 255-274
    • Gu H., .Z.1    Lee S., .Y.2
  • 46
    • 84866725086 scopus 로고    scopus 로고
    • Learning 3D object templates by hierarchical quantization of geometry and appearance spaces
    • IEEE, New York
    • Hu, W.: Learning 3D object templates by hierarchical quantization of geometry and appearance spaces. In: CVPR, pp. 2336-2343. IEEE, New York (2012)
    • (2012) CVPR , pp. 2336-2343
    • Hu, W.1
  • 47
    • 84866720197 scopus 로고    scopus 로고
    • Estimating the aspect layout of object categories
    • IEEE, New York
    • Xiang, Y.; Savarese, S.: Estimating the aspect layout of object categories. In: CVPR, pp. 3410-3417. IEEE, New York (2012)
    • (2012) CVPR , pp. 3410-3417
    • Xiang, Y.1    Savarese, S.2
  • 49
    • 50649097874 scopus 로고    scopus 로고
    • 3D generic object categorization, localization and pose estimation
    • Savarese, S.; Fei-Fei, L.: 3D generic object categorization, localization and pose estimation. In: ICCV, pp. 1-8 (2007)
    • (2007) ICCV , pp. 1-8
    • Savarese, S.1    Fei-Fei, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.