Local autocorrelation of similarities with subspaces for shift invariant scene classification

Pattern Recognition

Volumn 44, Issue 4, 2011, Pages 794-799

  Hotta, Kazuhiro ^a  

^a MEIJO UNIVERSITY   (Japan)

Author keywords

KPCA of visual words; Local autocorrelation; Scene classification; Shift invariance

Indexed keywords

BAG-OF-VISUAL WORDS; EFFECTIVE PROPERTY; KERNEL PRINCIPAL COMPONENT ANALYSIS; LOCAL AUTO-CORRELATION; LOCAL PARTS; SCENE CLASSIFICATION; SHIFT INVARIANCE; SHIFT INVARIANT; VISUAL WORD;

PRINCIPAL COMPONENT ANALYSIS;

AUTOCORRELATION;

EID: 78650294933     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2010.11.003     Document Type: Article

References (31)

1. A. Torralba Contextual priming for object detection International Journal of Computer Vision 53 2 2003 169 191
2. T. Ishihara, K. Hotta, H. Takahashi, Estimation of object position based on color and shape contextual information, in: Proceedings of the International Conference on Image Analysis and Processing, Lecture Notes in Computer Science, vol. 5716, 2009, pp. 5762.
3. L. Fei-Fei, P. Perona, A bayesian hierarchical model for learning natural scene categories, in: Proceedings of the IEEE CS Conference on Computer Vision and Pattern Recognition, 2005, pp. 524531. (Pubitemid 43897401)
4. J. Luo, M. Boutell, R. Gray, and C. Brown Image transform bootstrapping and its applications to semantic scene classification IEEE Transactions on Systems, Man, and CyberneticsPart B: Cybernetics 35 3 2005 563 570 (Pubitemid 40794867)
5. A. Bosch, A. Zisserman, X. Munoz, Scene classification via pLSA, in: Proceedings of the 9th European Conference on Computer Vision, 2006, pp. 517530. (Pubitemid 44029655)
6. S. Lazebnik, C. Schmid, J. Ponce, Beyond bags of features: spatial pyramid matching for recognizing natural scene categories, in: Proceedings of the IEEE CS Conference on Computer Vision and Pattern Recognition, 2006, pp. 21692178. (Pubitemid 44931582)
7. J.C. van Gemert, J.-M. Geusebroek, C.J. Veenman, A.W. Smeulders, Kernel codebooks for scene classification, in: Proceedings of the European Conference on Computer Vision, 2008, pp. 696709.
8. A. Bosch, A. Zisserman, and X. Munoz Scene classification using a hybrid generative/discriminative approach IEEE Transactions on Pattern Analysis and Machine Intelligence 30 4 2008 712 727 (Pubitemid 351559723)
9. K. Hotta, Scene classification based on multi-resolution orientation histogram of Gabor features, in: Proceedings of the International Conference on Computer Vision Systems, Lecture Notes in Compute Science, vol. 5008, 2008, pp. 291301. (Pubitemid 351775974)
10. K. Hotta, Scene classification based on local autocorrelation of similarities with subspaces, in: Proceedings of the IEEE International Conference on Image Processing, 2009, pp. 20532056.
11. K.-R. Mller, S. Mika, G. Rtsch, K. Tsuda, and B. Schlkopf An introduction to kernel-based learning algorithms IEEE Transactions on Neural Networks 12 2 2001 181 201 (Pubitemid 32371478)
12. B. Schlkopf, C. Burges, and A. Smola Advances in Kernel Methods: Support Vector Learning 1998 MIT Press
13. K. Hotta, Object categorization based on kernel principal component analysis of visual words, in: Proceedings of the IEEE Workshop on Applications of Computer Vision, 2008.
14. K. Hotta Non-linear feature extraction by linear principal component analysis using local kernel Pattern Recognition Recent Advances 2010 99 109
15. N. Otsu, T. Kurita, A new scheme for practical flexible and intelligent vision systems, in: Proceedings of the IAPR Workshop on Computer Vision, 1988, pp. 431435.
16. V. Vapnik Statistical Learning Theory 1998 John Wiley & Sons
17. -13 Scene categories database 〈 http://vision.cs.princeton.edu/ Databsets/SceneClass13.rar .
18. D. Lowe Distinctive image features from scale-invariant keypoints International Journal of Computer Vision 60 2 2004 91 110
19. L. Fei-Fei, R. Fergus, P. Perona, Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories, in: Proceedings of the CVPR Workshop of Generative Model Based Vision, 2004.
20. N. Dalal, B. Trigs, Histogram of oriented gradients for human detection, in: Proceedings of the IEEE CS Conference on Computer Vision and Pattern Recognition, 2005, pp. 886893. (Pubitemid 43897286)
21. J. Jones, and L. Palmer An evaluation of the two-dimensional Gabor filter model of simple receptive fields in the cat striate cortex Journal of Neurophysiology 58 1987 1233 1258 (Pubitemid 18023459)
22. B. Olshausen, and D. Field Emergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 13 1996 607 609 (Pubitemid 26177476)
23. A. Bell, and T. Sejnowski The 'independent components' of natural scenes are edge filters Vision Research 37 23 1997 3327 3338 (Pubitemid 27493806)
24. M. Lades, J.C. Vorbrggen, J. Buhmann, J. Lange, C.v.d. Malsburg, R.P. Wrtz, and W. Konen Distortion invariant object recognition in the dynamic link architecture IEEE Transactions on Computer 42 3 1993 300 311
25. T. Balachander, R. Kothari, Kernel based subspace pattern classification, in: Proceedings of the International Joint Conference on Neural Networks, vol. 5, 1999, pp. 31193122. (Pubitemid 30593542)
26. R. Debnath, and H. Takahashi Kernel selection for the support vector machine IEICE Transactions on Information and Systems E87-D 12 2004 2903 2904 (Pubitemid 40021366)
27. T. Kobayashi, N. Otsu, Action and simultaneous multiple-person identification using cubic higher-order local auto-correlation, in: Proceedings of the 17th International Conference on Pattern Recognition, 2004, pp. 741744.
28. B. Heisele, P. Ho, J. Wu, and T. Poggio Face recognition: component-based versus global approaches Computer Vision and Image Understanding 91 1/2 2003 6 21 (Pubitemid 36795765)
29. C.-W. Hsu, and C.-J. Lin A comparison of methods for multiclass support vector machines IEEE Transactions on Neural Networks 13 2 2002 415 425 (Pubitemid 34475042)
30. M. Pontil, and A. Verri Support vector machines for 3d object recognition IEEE Transactions on Pattern Analysis and Machine Intelligence 20 6 1998 637 646 (Pubitemid 128744848)
31. B. Schlkopf, C. Burges, V. Vapnik, Extracting support data for a given task, in: Proceedings of the 1st International Conference on Knowledge Discovery and Data Mining, 1995, pp. 252257.