Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 2004, 60(2): 91-110
[2]
Ahmed A, Yu Kai, Xu Wei, et al. Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks // Proc of the 10th European Conference on Computer Vision. Marseille, France, 2008: 69-82
[3]
Lazebnik S, Schmid C, Ponce J. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. New York, USA, 2006: 2169-2178
[4]
Yang Jianchao, Yu Kai, Gong Yihong, et al. Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA, 2009: 1794-1801
[5]
Olshausen B A, Field D J. Sparse Coding with an Over-Complete Basis Set: A Strategy Employed by V1? Vision Research, 1997, 37(23): 3311-3325
[6]
Boureau Y L, Bach F, LeCun Y, et al. Learning Mid-Level Features for Recognition // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, USA, 2010: 2559-2566
[7]
Fritz M, Black M J, Bradski G R, et al. An Additive Latent Feature Model for Transparent Object Recognition // Proc of the 23rd An-nual Conference on Neural Information Processing Systems. Vancouver, Canada, 2009: 558-566
[8]
Mutch J, Lowe D G. Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields. International Journal of Computer Vision, 2008, 80(1): 45-47
[9]
Rolls E, Deco G. Computational Neuroscience of Vision. Oxford, UK: Oxford University Press, 2002
[10]
Lee H, Grosse R, Ranganath R, et al. Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Repre-sentations // Proc of the 26th Annual International Conference on Machine Learning. Montreal, Canada, 2009: 609-616
[11]
Ranzato M A, Huang Fujie, Boureau Y L, et al. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition[EB/OL].[2012-05-30].http://www.cs.nyu.edu/~ylan/files/publi/ranzato-cvpr-07.pdf
[12]
Serre T, Wolf L, Bileschi S, et al. Robust Object Recognition with Cortex-Like Mechanisms. IEEE Trans on Pattern Analysis and Machine Intelligence, 2007, 29(3): 411-426
[13]
Sivic J, Russell B C, Efros A A, et al. Discovering Objects and Their Locations in Images // Proc of the 10th IEEE International Conference on Computer Vision. Beijing, China, 2005, I: 370-377
[14]
Blei D M, Ng A Y, Jordan M I. Latent Dirichlet Allocation. Journal of Machine Learning Research, 2003, 3(1): 993-1022
[15]
Blei D M, Griffiths T L, Jordan M I, et al. Hierarchical Topic Models and the Nested Chinese Restaurant Process[EB/OL]. [2012-07-25]. http://machinelearning.wustl.edu/mlpapers/paper_files/NIPS2003_AA03.pdf
[16]
Ferguson T S. A Bayesian Analysis of Some Nonparametric Problems. The Annals of Statistics, 1973, 1(3): 209-230
[17]
Heinrich G. Parameter Estimation for Text Analysis[EB/OL]. [2012-07-25]. http://www.arbylon.net/publications/text-est.pdf
[18]
Li Feifei, Fergus R, Perona P. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories. Computer Vision and Image Understanding, 2004, 106(1): 59-70
[19]
Kavukcuoglu K, Sermanet P, Boureau Y L, et al. Learning Convolutional Feature Hierarchies for Visual Recognition[EB/OL]. [2012-07-25]. http://yann.lecun.com/exdb/publis/pdf/koray-nips-10.pdf
[20]
Fidler S, Boben M, Leonardis A. Similarity-Based Cross-Layered Hierarchical Representation for Object Categorization[EB/OL].[2012-06-10].http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4587409&tag=1