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Volumn , Issue , 2010, Pages 2472-2479

Robust classification of objects, faces, and flowers using natural image statistics

Author keywords

[No Author keywords available]

Indexed keywords

CALTECH; DATA SETS; FACE DATABASE; FACE DETECTOR; FEATURE TYPES; NATURAL IMAGE STATISTICS; NATURAL IMAGES; PARTIAL VIEWS; PERFORMANCE DEGRADATION; ROBUST CLASSIFICATION; ROBUST PERFORMANCE; SPARSE CODING; TRANSLATION INVARIANCE; VISUAL ATTENTION; VISUAL TASKS;

EID: 77956006319     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5539947     Document Type: Conference Paper
Times cited : (179)

References (39)
  • 2
    • 51949090223 scopus 로고    scopus 로고
    • In defense of Nearest-Neighbor based image classification
    • June
    • O. Boiman, E. Shechtman, and M. Irani. In defense of Nearest-Neighbor based image classification. In CVPR 2008, June.
    • CVPR 2008
    • Boiman, O.1    Shechtman, E.2    Irani, M.3
  • 3
    • 84864039864 scopus 로고    scopus 로고
    • Saliency Based on Information Maximization
    • N. Bruce and J. Tsotsos. Saliency Based on Information Maximization. In NIPS 2006.
    • NIPS 2006
    • Bruce, N.1    Tsotsos, J.2
  • 4
    • 2442491808 scopus 로고    scopus 로고
    • Independent components of color natural scenes resemble V1 neurons in their spatial and color tuning
    • M. S. Caywood, B.Willmore, and D. J. Tolhurst. Independent components of color natural scenes resemble V1 neurons in their spatial and color tuning. Journal of Neurophysiology, 91:2859-73, 2004.
    • (2004) Journal of Neurophysiology , vol.91 , pp. 2859-2873
    • Caywood, M.S.1    Willmore, B.2    Tolhurst, D.J.3
  • 6
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
    • L. Fei-fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In CVPR 2004.
    • CVPR 2004
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 7
    • 0000929221 scopus 로고
    • What is the goal of sensory coding?
    • D. Field. What is the goal of sensory coding? Neural Computation, 6:559-601, 1994.
    • (1994) Neural Computation , vol.6 , pp. 559-601
    • Field, D.1
  • 8
    • 85067032737 scopus 로고    scopus 로고
    • On Feature Combination for Multiclass Object Classification
    • P. V. Gehler and S. Nowozin. On Feature Combination for Multiclass Object Classification. In ICCV 2009.
    • ICCV 2009
    • Gehler, P.V.1    Nowozin, S.2
  • 9
    • 0035510910 scopus 로고    scopus 로고
    • Making choices: The neurophysiology of visual-saccadic decision making
    • P. Glimcher. Making choices: the neurophysiology of visual-saccadic decision making. Trends in Neurosciences, 24:654-659, 2001.
    • (2001) Trends in Neurosciences , vol.24 , pp. 654-659
    • Glimcher, P.1
  • 10
    • 33745226951 scopus 로고    scopus 로고
    • Can the theory of "whitening" explain the center-surround properties of retinal ganglion cell receptive fields?
    • D. Graham, D. Chandler, and D. Field. Can the theory of "whitening" explain the center-surround properties of retinal ganglion cell receptive fields? Vision Research, 46:2901-2913, 2006.
    • (2006) Vision Research , vol.46 , pp. 2901-2913
    • Graham, D.1    Chandler, D.2    Field, D.3
  • 13
    • 0035286497 scopus 로고    scopus 로고
    • Computational Modelling of Visual Attention
    • L. Itti and C. Koch. Computational Modelling of Visual Attention. Nature Reviews Neurosciece, 2:194-203, 2001.
    • (2001) Nature Reviews Neurosciece , vol.2 , pp. 194-203
    • Itti, L.1    Koch, C.2
  • 14
    • 33750096193 scopus 로고    scopus 로고
    • Efficient Variant of Algorithm FastICA for Independent Component Analysis Attaining the Cramér-Rao Lower Bound
    • Z. Koldovský, P. Tichavský, and E. Oja. Efficient Variant Of Algorithm FastICA For Independent Component Analysis Attaining The Cramér-Rao Lower Bound. IEEE Trans. on Neural Networks, 17:1090-1095, 2006.
    • (2006) IEEE Trans. on Neural Networks , vol.17 , pp. 1090-1095
    • Koldovský, Z.1    Tichavský, P.2    Oja, E.3
  • 16
    • 33745854718 scopus 로고    scopus 로고
    • A Maximum Entropy Framework for Part-Based Texture and Object Recognition
    • S. Lazebnik, C. Schmid, and J. Ponce. A Maximum Entropy Framework for Part-Based Texture and Object Recognition. In ICCV 2005.
    • ICCV 2005
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 17
    • 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.
    • CVPR 2006
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 20
    • 34547669000 scopus 로고    scopus 로고
    • Uncorrelated linear discriminant analysis based on weighted pairwise Fisher criterion
    • Y. Liang, C. Li, W. Gong, and Y. Pan. Uncorrelated linear discriminant analysis based on weighted pairwise Fisher criterion. Pattern Recognition, 40:3606-3615, 2007.
    • (2007) Pattern Recognition , vol.40 , pp. 3606-3615
    • Liang, Y.1    Li, C.2    Gong, W.3    Pan, Y.4
  • 21
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scaleinvariant keypoints
    • D. Lowe. Distinctive image features from scaleinvariant keypoints. IJCV, 60:91-110, 2004.
    • (2004) IJCV , vol.60 , pp. 91-110
    • Lowe, D.1
  • 24
    • 33845569574 scopus 로고    scopus 로고
    • Multiclass Object Recognition with Sparse, Localized Features
    • J. Mutch and D. Lowe. Multiclass Object Recognition with Sparse, Localized Features. In CVPR 2006, pages 11-18, 2006.
    • (2006) CVPR 2006 , pp. 11-18
    • Mutch, J.1    Lowe, D.2
  • 27
    • 31844436661 scopus 로고    scopus 로고
    • Q-learning of sequential attention for visual object recognition from informative local descriptors
    • L. Paletta, G. Fritz, and C. Seifert. Q-learning of sequential attention for visual object recognition from informative local descriptors. In ICML 2005.
    • ICML 2005
    • Paletta, L.1    Fritz, G.2    Seifert, C.3
  • 29
    • 79952501854 scopus 로고    scopus 로고
    • Establishing Good Benchmarks and Baselines for Face Recognition
    • N. Pinto, J. DiCarlo, and D. Cox. Establishing Good Benchmarks and Baselines for Face Recognition. In ECCV 2008.
    • ECCV 2008
    • Pinto, N.1    DiCarlo, J.2    Cox, D.3
  • 30
  • 31
    • 0033316361 scopus 로고    scopus 로고
    • Hierarchical models of object recognition in cortex
    • M. Riesenhuber and T. Poggio. Hierarchical models of object recognition in cortex. Nature Neuroscience, 2:1019-1025, 1999.
    • (1999) Nature Neuroscience , vol.2 , pp. 1019-1025
    • Riesenhuber, M.1    Poggio, T.2
  • 33
    • 51949094985 scopus 로고    scopus 로고
    • Looking around the backyard helps to recognize faces and digits
    • H. Shan and G. Cottrell. Looking around the backyard helps to recognize faces and digits. In CVPR 2008.
    • CVPR 2008
    • Shan, H.1    Cottrell, G.2
  • 34
    • 56649114397 scopus 로고    scopus 로고
    • Face Recognition with Disguise and Single Gallery Images
    • R. Singh, M. Vatsa, and A. Noore. Face Recognition with Disguise and Single Gallery Images. Image and Vision Computing, 27:245-257, 2007.
    • (2007) Image and Vision Computing , vol.27 , pp. 245-257
    • Singh, R.1    Vatsa, M.2    Noore, A.3
  • 35
    • 31744441556 scopus 로고    scopus 로고
    • A globally convergent and consistent method for estimating the shape parameter of a generalized Gaussian distribution
    • K. Song. A globally convergent and consistent method for estimating the shape parameter of a generalized Gaussian distribution. IEEE Transactions on Information Theory, 52:510-527, 2006.
    • (2006) IEEE Transactions on Information Theory , vol.52 , pp. 510-527
    • Song, K.1
  • 36
    • 0032492432 scopus 로고    scopus 로고
    • Independent component filters of natural images compared with simple cells in primary visual cortex
    • J. Van Hateren and A. Van Der Schaaf. Independent component filters of natural images compared with simple cells in primary visual cortex. Proc R Soc London B., 265:359-366, 1998.
    • (1998) Proc R Soc London B , vol.265 , pp. 359-366
    • Van Hateren, J.1    Van Der Schaaf, A.2
  • 38
    • 70450209196 scopus 로고    scopus 로고
    • Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification
    • J. Yang, K. Yu, Y. Gong, and T. Huang. Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification. In CVPR 2009.
    • CVPR 2009
    • Yang, J.1    Yu, K.2    Gong, Y.3    Huang, T.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.