Hierarchical matching pursuit for image classification: Architecture and fast algorithms

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Bo, Liefeng ^a   Ren, Xiaofeng ^b   Fox, Dieter ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

^b INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DEEP LEARNING; FORESTRY; IMAGE CODING; IMAGE REPRESENTATION; NETWORK ARCHITECTURE; OBJECT RECOGNITION; SUPPORT VECTOR MACHINES;

FAST ALGORITHMS; FEATURE HIERARCHIES; HIERARCHICAL MATCHING; IMAGES CLASSIFICATION; LAYER BY LAYER; MATCHING PURSUIT; MAX-POOLING; ORTHOGONAL MATCHING PURSUIT; PERFORMANCE; SPATIAL PYRAMIDS;

IMAGE CLASSIFICATION;

ALGORITHMS; CLASSIFICATION; FORESTRY; IMAGE ANALYSIS;

EID: 85162387004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. M. Aharon, M. Elad, and A. Bruckstein. K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation. IEEE Transactions on Signal Processing, 54(11):4311-4322, 2006.
2. L. Bo, X. Ren, and D. Fox. Kernel Descriptors for Visual Recognition. In NIPS, 2010.
3. L. Bo and C. Sminchisescu. Efficient Match Kernel between Sets of Features for Visual Recognition. In NIPS, 2009.
4. O. Boiman, E. Shechtman, and M. Irani. In Defense of Nearest-Neighbor based Image Classification. In CVPR, 2008.
5. Y. Boureau, F. Bach, Y. LeCun, and J. Ponce. Learning Mid-level Features for Recognition. In CVPR, 2010.
6. A. Coates and A. Ng. The Importance of Encoding versus Training with Sparse Coding and Vector Quantization. In ICML, 2011.
7. G. Davis, S. Mallat, and M. Avellaneda. Adaptive Greedy Approximations. Constructive Approximation, 13(1):57-98, 1997.
8. P. Gehler and S. Nowozin. On Feature Combination for Multiclass Object Classification. In ICCV, 2009.
9. G. Hinton, S. Osindero, and Y. Teh. A Fast Learning Algorithm for Deep Belief Nets. Neural Computation, 18(7):1527-1554, 2006.
10. P. Jain, B. Kulis, and K. Grauman. Fast Image Search for Learned Metrics. In CVPR, 2008.
11. K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun. What is the Best Multi-Stage Architecture for Object Recognition? In ICCV, 2009.
12. K. Kavukcuoglu, M. Ranzato, R. Fergus, and Y. LeCun. Learning Invariant Features through Topographic Filter Maps. In CVPR, 2009.
13. K. Kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, and Y. LeCun. Learning Convolutional Feature Hierarchies for Visual Recognition. In NIPS. 2010.
14. S. Lazebnik, C. Schmid, and J. Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In CVPR, 2006.
15. H. Lee, A. Battle, R. Raina, and A. Ng. Efficient Sparse Coding Algorithms. In NIPS. 2007.
16. H. Lee, R. Grosse, R. Ranganath, and A. Ng. Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations. In ICML, 2009.
17. L. Li and L. Fei-Fei. What, Where and Who? Classifying Event by Scene and Object Recognition. In ICCV, 2007.
18. L. Li, H. Su, E. Xing, and L. Fei-Fei. Object Bank: A High-Level Image Representation for Scene Classification and Semantic Feature Sparsification. In NIPS, 2010.
19. Y. Pati, R. Rezaiifar, and P. Krishnaprasad. Orthogonal Matching Pursuit: Recursive Function Approximation with Applications toWavelet Decomposition. In The Twenty-Seventh Asilomar Conference on Signals, Systems and Computers, pages 40-44, 1993.
20. A. Quattoni and A. Torralba. Recognizing Indoor Scenes. In CVPR, 2009.
21. R. Rubinstein, A. Bruckstein, and M Elad. Dictionaries for Sparse Representation Modeling. Proceedings of the IEEE, 98(6):4311-4322, 2010.
22. R. Rubinstein, M. Zibulevsky, and M. Elad. Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit. Technical report, 2008.
23. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Guo. Locality-constrained Linear Coding for Image Classification. In CVPR, 2010.
24. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear Spatial Pyramid Matching using Sparse Coding for Image Classification. In CVPR, 2009.
25. K. Yu, Y. Lin, and J. Lafferty. Learning Image Representations from the Pixel Level via Hierarchical Sparse Coding. In CVPR, 2011.
26. M. Zeiler, D. Krishnan, G. Taylor, and R. Fergus. Deconvolutional Networks. In CVPR, 2010.