Good practice in large-scale learning for image classification

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 3, 2014, Pages 507-520

  Akata, Zeynep ^a,b   Perronnin, Florent ^a   Harchaoui, Zaid ^b   Schmid, Cordelia ^b  

^a XEROX RESEARCH CENTRE EUROPE   (France)

^b INRIA RHÔNE ALPES   (France)

Author keywords

fine grained visual categorization; image classification; Large scale; ranking; stochastic learning; SVM

Indexed keywords

EID: 84894567325     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.146     Document Type: Article

References (90)

1. E.L. Allwein, R.E. Schapire, and Y. Singer, "Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers, " Proc. Int'l Conf. Machine Learning (ICML), 2000.
2. B. Bai, J. Weston, D. Grangier, R. Collobert, O. Chapelle, and K. Weinberger, "Supervised Semantic Indexing, " Proc. 18th ACM Conf. Information and Knowledge Management (CIKM), 2009.
3. P.L. Bartlett, M.I. Jordan, and J.D. McAuliffe, "Convexity Classification, and Risk Bounds, " Proc. Conf. Neural Information Processing Systems (NIPS), 2003.
4. S. Bengio, J. Weston, and D. Grangier, "Label Embedding Trees for Large Multi-Class Tasks, " Proc. Conf. Neural Information Processing Systems (NIPS), 2010.
5. Y. Bengio, A. Courville, and P. Vincent, Representation Learning: A Rev. and New Perspectives.
6. A. Berg, J. Deng, and L. Fei-Fei, ILSVRC, http://www.image-net. org/challenges/LSVRC/2010/index, 2010.
7. A. Bergamo, L. Torresani, and A. Fitzgibbon, "PICODES: Learning a Compact Code for Novel-Category Recognition, " Proc. Conf. Neural Information Processing Systems (NIPS), 2011.
8. A. Beygelzimer, V. Dani, T.P. Hayes, J. Langford, and B. Zadrozny, "Error Limiting Reductions between Classification Tasks, " Proc. Int'l Conf. Machine Learning (ICML), 2005.
9. A. Bordes, L. Bottou, P. Gallinari, and J. Weston, "Solving Multiclass Support Vector Machines with LaRank, " Proc. Int'l Conf. Machine Learning (ICML), 2007.
10. L. Bottou, SGD, http://leon.bottou.org/projects/sgd, 2013.
11. L. Bottou and O. Bousquet, "The Tradeoffs of Large Scale Learning, " Proc. Conf. Neural Information Processing Systems (NIPS), 2007.
12. Y.-L. Bourreau, F. Bach, Y. LeCun, and J. Ponce, "Learning Mid-Level Features for Recognition, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2010.
13. G. Burghouts and J.-M. Geusebroek, "Performance Evaluation of Local Colour Invariants, " Computer Vision and Image Understanding, vol. 113, pp. 48-62, 2009.
14. P.K. Chan and S.J. Stolfo, "On the Accuracy of Meta-Learning for Scalable Data Mining, " J. Intelligent Information Systems, vol. 8, pp. 5-28, 1997. (Pubitemid 127507743)
15. C.-C. Chang and C.-J. Lin, "LIBSVM: A Library for Support Vector Machines, " ACM Trans. Intelligent Systems and Technology, vol. 2, http://www.csie.ntu.edu.tw/cjlin/libsvm, 2011.
16. K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman, "The Devil Is in the Details: An Evaluation of Recent Feature Encoding Methods, " Proc. British Machine Vision Conf. (BMVC), 2011.
17. K. Crammer and Y. Singer, "On the Algorithmic Implementation of Multiclass Kernel-Based Vector Machines, " The J. Machine Learning Research, vol. 2, pp. 265-292, 2002.
18. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints, " Proc. ECCV Workshop Statistical Learning in Computer Vision Workshop, 2004.
19. J. Dean, G. Corrado, R. Monga, M. Devin, Q. Le, M. Mao, M. Ranzato, A. Senior, P. Tucker, K. Yang, and A. Ng, "Large Scale Distributed Deep Networks, " Proc. Conf. Neural Information Processing Systems (NIPS), 2012.
20. J. Deng, A. Berg, K. Li, and L. Fei-Fei, "What Does Classifying More Than 10, 000 Image Categories Tell Us?" Proc. 11th European Conf. Computer Vision (ECCV), 2010.
21. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, "Imagenet: A Large-Scale Hierarchical Image Database, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2009.
22. J. Deng, S. Satheesh, A. Berg, and L. Fei-Fei, "Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition, " Proc. Conf. Neural Information Processing Systems (NIPS), 2011.
23. T. Deselaers and V. Ferrari, "Visual and Semantic Similarity in Imagenet, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
24. T.G. Dietterich and G. Bakiri, "Solving Multiclass Learning Problems via Error-Correcting Output Codes, " J. Artificial Intelligence Research, vol. 2, pp. 263-286, 1995.
25. M. Everingham, L.V. Gool, C. Williams, J. Winn, and A. Zisserman, "The Pascal Visual Object Classes (VOC) Challenge, " Int'l J. Computer Vision, vol. 88, pp. 303-338, 2010.
26. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin, "LIBLINEAR: A Library for Large Linear Classification, " The J. Machine Learning Research, vol. 9, pp. 1871-1874, 2008.
27. J. Farquhar, S. Szedmak, H. Meng, and J. Shawe-Taylor, "Improving Bag-of-Keypoints Image Categorisation, " technical report, Univ. of Southampton, 2005.
28. V. Franc and S. Sonnenburg, "Optimized Cutting Plane Algorithm for Support Vector Machines, " Proc. Int'l Conf. Machine Learning (ICML), 2008.
29. T. Gao and D. Koller, "Discriminative Learning of Relaxed Hierarchy for Large-Scale Visual Recognition, " Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2011.
30. J. Gehrke, R. Ramakrishnan, and V. Ganti, "Rainforest-A Framework for Fast Decision Tree Construction of Large Data Sets, " Proc. Data Mining and Knowledge Discovery (DMKD), 2000.
31. Y. Gong and S. Lazebnik, "Comparing Data-Dependent and Data-Independent Embeddings for Classification and Ranking of Internet Images, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
32. D. Grangier, F. Monay, and S. Bengio, "A Discriminative Approach for the Retrieval of Images from Text Queries, " Proc. 17th European Conf. Machine Learning (ECML), 2006.
33. C.-J. Hsieh, K.-W. Chang, C.-J. Lin, S.S. Keerthi, and S. Sundararajan, "A Dual Coordinate Descent Method for Large-Scale Linear SVM, " Proc. Int'l Conf. Machine Learning (ICML), 2008.
34. K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun, "What Is the Best Multi-Stage Architecture for Object Recognition?" Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2009.
35. H. Jégou, M. Douze, and C. Schmid, "Product Quantization for Nearest Neighbor Search, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 1, pp. 117-128, Jan. 2011.
36. H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez, and C. Schmid, "Aggregating Local Image Descriptors Into Compact Codes, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 9, pp. 1704-1716, Sept. 2012.
37. T. Joachims, "Making Large-Scale Support Vector Machine Learning Practical, " Advances in Kernel Methods, MIT Press, 1999.
38. T. Joachims, "Optimizing Search Engines Using Clickthrough Data, " Proc. Eighth ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 133-142, 2002.
39. T. Joachims, "Training Linear SVMs in Linear Time, " Proc. 12th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, 2006.
40. A. Krizhevsky, I. Sutskever, and G. Hinton, "Image Classification with Deep Convolutional Neural Networks, " Proc. Conf. Neural Information Processing Systems (NIPS), 2012.
41. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2006.
42. Q. Le, M. Ranzato, R. Monga, M. Devin, K. Chen, G. Corrado, J. Dean, and A. Ng, "Building High-Level Features Using Large Scale Unsupervised Learning, " Proc. Int'l Conf. Machine Learning (ICML), 2012.
43. Y. LeCun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel, "Handwritten Digit Recognition with a Back-Propagation Network, " Proc. Conf. Neural Information Processing Systems (NIPS), 1989.
44. Y. LeCun, L. Bottou, G. Orr, and K. Muller, "Efficient Backprop, " Neural Networks: Tricks of the Trade, Springer, 1998.
45. Y. LeCun, F. Huang, and L. Bottou, "Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2004.
46. T. Lee, Y. Lin, and G. Wahba, "Multicategory Support Vector Machines: Theory and Application to the Classification of Micro-array Data and Satellite Radiance Data, " J. Am. Statistical Assoc., 2004.
47. L. Li, H. Su, E. Xing, and L. Fei-Fei, "Object Bank: A High-Level Image Representation for Scene Classification and Semantic Feature Sparsification, " Proc. Conf. Neural Information Processing Systems (NIPS), 2010.
48. Y. Lin, F. Lv, S. Zhu, M. Yang, T. Cour, K. Yu, L. Cao, and T. Huang, "Large-Scale Image Classification: Fast Feature Extraction and SVM Training, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
49. Y. Lin, F. Lv, S. Zhu, K. Yu, M. Yang, and T. Cour, "Large-Scale Image Classification: Fast Feature Extraction and SVM Training, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
50. D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints, " Int'l J. Computer Vision, vol. 60, pp. 91-110, 2004.
51. S. Maji and A. Berg, "Max-Margin Additive Classifiers for Detection, " Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2009.
52. M. Marszalek and C. Schmid, "Constructing Category Hierarchies for Visual Recognition, " Proc. 10th European Conf. Computer Vision (ECCV), 2008.
53. M. Mehta, R. Agrawal, and J. Rissanen, "Sliq: A Fast Scalable Classifier for Data Mining, " Proc. Int'l Conf. Extending Database Technology (EDBT), 1996.
54. S. Nowozin and C. Lampert, "Structured Learning and Prediction in Computer Vision, " Foundations and Trends in Computer Graphics and Vision, vol. 6, pp. 185-365, 2011.
55. F. Perronnin, Z. Akata, Z. Harchaoui, and C. Schmid, "Towards Good Practice in Large-Scale Learning for Image Classification, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2012.
56. F. Perronnin and C. Dance, "Fisher Kernels on Visual Vocabularies for Image Categorization, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2007.
57. F. Perronnin, J. Sánchez, and Y. Liu, "Large-Scale Image Categorization with Explicit Data Embedding, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2010.
58. F. Perronnin, J. Sánchez, and T. Mensink, "Improving the Fisher Kernel for Large-Scale Image Classification, " Proc. 11th European Conf. Computer Vision (ECCV), 2010.
59. J.C. Platt, "Fast Training of Support Vector Machines Using Sequential Minimal Optimization, " Advances in Kernel Methods, MIT Press, 1999.
60. M. Rastegari, C. Fang, and L. Torresani, "Scalable Object-Class Retrieval with Approximate and Top-K Ranking, " Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2011.
61. R. Rifkin and A. Klautau, "In Defense of One-vs-All Classification, " The J. Machine Learning Research, vol. 5, pp. 101-141, 2004.
62. M. Rohrbach, M. Stark, and B. Schiele, "Evaluating Knowledge Transfer and Zero-Shot Learning in a Large-Scale Setting, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
63. L. Rokach and O. Maimon, "Top-Down Induction of Decision Trees Classifiers-A Survey, " IEEE Trans. Systems, Man, and Cybernetics, vol. 35, no. 4, pp. 476-487, Nov. 2005. (Pubitemid 41638167)
64. B.C. Russell, A. Torralba, K.P. Murphy, and W.T. Freeman, "LabelME: A Database and Web-Based Tool for Image Annotation, " Int'l J. Computer Vision, vol. 77, pp. 157-173, 2008.
65. S.L. Salzberg, "On Comparing Classifiers: Pitfalls Toavoid and a Recommended Approach, " Data Mining and Knowledge Discovery, vol. 1, pp. 317-328, 1997.
66. J. Sánchez and F. Perronnin, "High-Dimensional Signature Compression for Large-Scale Image Classification, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2011.
67. S. Shalev-Shwartz, Y. Singer, and N. Srebro, "Pegasos: Primal Estimate Sub-Gradient Solver for SVM, " Proc. Int'l Conf. Machine Learning (ICML), 2007.
68. D.J. Sheskin, Handbook of Parametric and Nonparametric Statistical Procedures, fourth ed. Chapman & Hall/CRC, 2007.
69. J. Sivic and A. Zisserman, "Video Google: A Text Retrieval Approach to Object Matching in Videos, " Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2003.
70. D. Tao, X. Tang, X. Li, and X. Wu, "Asymmetric Bagging and Random Subspace for Support Vector Machines-Based Relevance Feedback in Image Retrieval, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 7, pp. 1088-1099, July 2006.
71. A. Tewari and P.L. Bartlett, "On the Consistency of Multiclass Classification Methods, " The J. Machine Learning Research, vol. 8, pp. 1007-1025, 2007. (Pubitemid 46798410)
72. A. Torralba, R. Fergus, and W. Freeman, "80 Million Tiny Images: A Large Data Set for Non-Parametric Object and Scene Recognition, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 11, pp. 1958-1970, Nov. 2008.
73. L. Torresani, M. Szummer, and A. Fitzgibbon, "Efficient Object Category Recognition Using Classemes, " Proc. 11th European Conf. Computer Vision (ECCV), 2010.
74. I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, "Large Margin Methods for Structured and Interdependent Output Variables, " The J. Machine Learning Research, vol. 6, pp. 1453-1484, 2005.
75. N. Usunier, D. Buffoni, and P. Gallinari, "Ranking with Ordered Weighted Pairwise Classification, " Proc. Int'l Conf. Machine Learning (ICML), 2009.
76. J.C. van Gemert, C.J. Veenman, A.W.M. Smeulders, and J.M. Geusebroek, "Visual Word Ambiguity, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 7, pp. 1271-1283, July 2010.
77. A. Vedaldi and A. Zisserman, "Efficient Additive Kernels via Explicit Feature Maps, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2010.
78. A. Vedaldi and A. Zisserman, "Sparse Kernel Approximations for Efficient Classification and Detection, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2012.
79. V. Vural and J.G. Dy, "A Hierarchical Method for Multi-Class Support Vector Machines, " Proc. Int'l Conf. Machine Learning (ICML), 2004.
80. G. Wang, D. Hoiem, and D. Forsyth, "Learning Image Similarity from Flickr Groups Using Stochastic Intersection Kernel Machines, " Proc. IEEE Int'l Conf. Computer Vision (ICCV), 2009.
81. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong, "Locality-Constrained Linear Coding for Image Classification, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2010.
82. J. Weston, S. Bengio, and N. Usunier, "Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embed-dings, " Proc. European Conf. Machine Learning (ECML), 2010.
83. J. Weston, S. Bengio, and N. Usunier, "WSABIE: Scaling up to Large Vocabulary Image Annotation, " Proc. 22nd Int'l Joint Conf. Artificial Intelligence, 2011.
84. J. Weston and C. Watkins, "Multi-Class Support Vector Machines, " technical report, Dept. of Computer Science, Royal Holloway, Univ. of London, 1998.
85. J. Weston and C. Watkins, "Support Vector Machines for Multi-Class Pattern Recognition, " Proc. European Symp. Artificial Neural Networks (ESANN), 1999.
86. J. Xu, T. Liu, M. Lu, H. Li, and W. Ma, "Directly Optimizing Evaluation Measures in Learning to Rank, " Proc. 31st Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), 2008.
87. J. Yang, K. Yu, Y. Gong, and T.S. Huang, "Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification, " Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2009.
88. Y. Yue, T. Finley, F. Radlinski, and T. Joachims, "A Support Vector Method for Optimizing Average Precision, " Proc. 31st Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), 2007.
89. B. Zhao, L. Fei-Fei, and E. Xing, "Large-Scale Category Structure Aware Image Categorization, " Proc. Conf. Neural Information Processing Systems (NIPS), 2011.
90. Z. Zhou, K. Yu, T. Zhang, and T. Huang, "Image Classification Using Super-Vector Coding of Local Image Descriptors, " Proc. 11th European Conf. Computer Vision (ECCV), 2010.