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Volumn , Issue , 2010, Pages

Kernel descriptors for visual recognition

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; GRAPHIC METHODS; LOCAL BINARY PATTERN; PRINCIPAL COMPONENT ANALYSIS;

EID: 85162018819     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (290)

References (28)
  • 1
    • 78149331496 scopus 로고    scopus 로고
    • Efficient match Kernel between sets of features for visual recognition
    • L. Bo and C. Sminchisescu. Efficient Match Kernel between Sets of Features for Visual Recognition. In NIPS, 2009.
    • (2009) NIPS
    • Bo, L.1    Sminchisescu, C.2
  • 2
    • 51949090223 scopus 로고    scopus 로고
    • In defense of nearest-neighbor based image classification
    • O. Boiman, E. Shechtman, and M. Irani. In defense of nearest-neighbor based image classification. In CVPR, 2008.
    • (2008) CVPR
    • Boiman, O.1    Shechtman, E.2    Irani, M.3
  • 3
    • 33645146449 scopus 로고    scopus 로고
    • Histograms of oriented gradients for human detection
    • N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
    • (2005) CVPR
    • Dalal, N.1    Triggs, B.2
  • 5
    • 51949101231 scopus 로고    scopus 로고
    • A discriminatively trained, multiscale, deformable part model
    • P. Felzenszwalb, D. McAllester, and D. Ramanan. A discriminatively trained, multiscale, deformable part model. In CVPR, 2008.
    • (2008) CVPR
    • Felzenszwalb, P.1    McAllester, D.2    Ramanan, D.3
  • 6
    • 85067032737 scopus 로고    scopus 로고
    • On feature combination for multiclass object classification
    • P. Gehler and S. Nowozin. On feature combination for multiclass object classification. In ICCV, 2009.
    • (2009) ICCV
    • Gehler, P.1    Nowozin, S.2
  • 7
    • 33745855044 scopus 로고    scopus 로고
    • The pyramid match kernel: Discriminative classification with sets of image features
    • K. Grauman and T. Darrell. The pyramid match kernel: discriminative classification with sets of image features. In ICCV, 2005.
    • (2005) ICCV
    • Grauman, K.1    Darrell, T.2
  • 9
    • 77953183471 scopus 로고    scopus 로고
    • What is the best multi-stage architecture for object recognition?
    • K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun. What is the best multi-stage architecture for object recognition? In ICCV, 2009.
    • (2009) ICCV
    • Jarrett, K.1    Kavukcuoglu, K.2    Ranzato, M.3    Lecun, Y.4
  • 10
    • 70450177775 scopus 로고    scopus 로고
    • Learning invariant features through topographic filter maps
    • K. Kavukcuoglu, M. Ranzato, R. Fergus, and Y. LeCun. Learning invariant features through topographic filter maps. In CVPR, 2009.
    • (2009) CVPR
    • Kavukcuoglu, K.1    Ranzato, M.2    Fergus, R.3    Lecun, Y.4
  • 11
    • 1942452419 scopus 로고    scopus 로고
    • A kernel between sets of vectors
    • R. Kondor and T. Jebara. A kernel between sets of vectors. In ICML, 2003.
    • (2003) ICML
    • Kondor, R.1    Jebara, T.2
  • 13
    • 33845572523 scopus 로고    scopus 로고
    • Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
    • S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006.
    • (2006) CVPR
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 14
    • 71149119164 scopus 로고    scopus 로고
    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • H. Lee, R. Grosse, R. Ranganath, and A. Ng. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In ICML, 2009.
    • (2009) ICML
    • Lee, H.1    Grosse, R.2    Ranganath, R.3    Ng, A.4
  • 15
    • 51749099542 scopus 로고    scopus 로고
    • One-shot learning of object categories
    • F. Li, R. Fergus, and P. Perona. One-shot learning of object categories. IEEE PAMI, 2006.
    • (2006) IEEE PAMI
    • Li, F.1    Fergus, R.2    Perona, P.3
  • 16
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60:91-110, 2004.
    • (2004) IJCV , vol.60 , pp. 91-110
    • Lowe, D.1
  • 17
    • 24644504191 scopus 로고    scopus 로고
    • Mercer kernels for object recognition with local features
    • S. Lyu. Mercer kernels for object recognition with local features. In CVPR, 2005.
    • (2005) CVPR
    • Lyu, S.1
  • 18
    • 27644547620 scopus 로고    scopus 로고
    • A performance evaluation of local descriptors
    • K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE PAMI, 27(10):1615-1630, 2005.
    • (2005) IEEE PAMI , vol.27 , Issue.10 , pp. 1615-1630
    • Mikolajczyk, K.1    Schmid, C.2
  • 19
    • 0036647193 scopus 로고    scopus 로고
    • Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
    • T. Ojala, M. Pietikäinen, and T. Mäenpää. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE PAMI, 24(7):971-987, 2002.
    • (2002) IEEE PAMI , vol.24 , Issue.7 , pp. 971-987
    • Ojala, T.1    Pietikäinen, M.2    Mäenpää, T.3
  • 20
    • 0035328421 scopus 로고    scopus 로고
    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • A. Oliva and A. Torralba. Modeling the shape of the scene: A holistic representation of the spatial envelope. IJCV, 42(3):145-175, 2001.
    • (2001) IJCV , vol.42 , Issue.3 , pp. 145-175
    • Oliva, A.1    Torralba, A.2
  • 21
    • 84879850729 scopus 로고    scopus 로고
    • Factored 3-way restricted boltzmann machines for modeling natural images
    • M. Ranzato, Krizhevsky A., and G. Hinton. Factored 3-way restricted boltzmann machines for modeling natural images. In AISTATS, 2010.
    • (2010) AISTATS
    • Ranzato, M.1    Krizhevsky, A.2    Hinton, G.3
  • 22
    • 77955989954 scopus 로고    scopus 로고
    • Modeling pixel means and covariances using factorized third-order boltzmann machines
    • M. Ranzato and G. Hinton. Modeling pixel means and covariances using factorized third-order boltzmann machines. In CVPR, 2010.
    • (2010) CVPR
    • Ranzato, M.1    Hinton, G.2
  • 23
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Schölkopf, A. Smola, and K. Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.3
  • 25
    • 54749092170 scopus 로고    scopus 로고
    • 80 million tiny images: A large data set for nonparametric object and scene recognition
    • A. Torralba, R. Fergus, and W. Freeman. 80 million tiny images: A large data set for nonparametric object and scene recognition. IEEE PAMI, 30(11):1958-1970, 2008.
    • (2008) IEEE PAMI , vol.30 , Issue.11 , pp. 1958-1970
    • Torralba, A.1    Fergus, R.2    Freeman, W.3
  • 26
    • 77955996870 scopus 로고    scopus 로고
    • Locality-constrained linear coding for image classification
    • J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Guo. Locality-constrained linear coding for image classification. In CVPR, 2010.
    • (2010) CVPR
    • Wang, J.1    Yang, J.2    Yu, K.3    Lv, F.4    Huang, T.5    Guo, Y.6
  • 28
    • 85162016725 scopus 로고    scopus 로고
    • Deep learning with kernel regularization for visual recognition
    • K. Yu, W. Xu, and Y. Gong. Deep learning with kernel regularization for visual recognition. In NIPS, 2008.
    • (2008) NIPS
    • Yu, K.1    Xu, W.2    Gong, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.