RALF: A reinforced active learning formulation for object class recognition

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 3626-3633

  Ebert, Sandra ^a   Fritz, Mario ^a   Schiele, Bernt ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CLASSIFICATION SCHEME; CLASSIFICATION TASKS; DATA SETS; DENSITY-BASED; EXPLORATION AND EXPLOITATION; LEARNING PROCESS; MARKOV DECISION PROCESSES; OBJECT CLASS RECOGNITION; PRIOR INFORMATION; SAMPLING STRATEGIES; TIME VARYING;

COMPUTER VISION; DATA PROCESSING; DIGITAL STORAGE; MARKOV PROCESSES; REINFORCEMENT LEARNING;

OBJECT RECOGNITION;

EID: 84866645923     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6248108     Document Type: Conference Paper

References (25)

1. Y. Baram, R. El-yaniv, and K. Luz. Online Choice of Active Learning Algorithms. JMLR, 5:255-291, 2004. 1, 2, 3
2. A. Bondu, V. Lemaire, and M. Boullé. Exploration vs. exploitation in active learning: a Bayesian approach. In IJCNN, 2010. 1, 2
3. N. Cebron and M. R. Berthold. Active learning for object classification: from exploration to exploitation. DMKD, 18(2):283-299, 2009. 1, 2, 3, 4
4. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005. 3
5. S. Dasgupta and D. Hsu. Hierarchical sampling for active learning. In ICML, 2008. 2
6. P. Donmez and J. Carbonell. Dual strategy active learning. In ECML, 2007. 2
7. S. Ebert, D. Larlus, and B. Schiele. Extracting Structures in Image Collections for Object Recognition. In ECCV, 2010. 3
8. M. Everingham, L. Van Gool, and C. K.Williams. The PASCAL VOC, 2008. 3
9. L. Fei-Fei, R. Fergus, and P. Perona. One-shot learning of object categories. TPAMI, 28(4):594-611, 2006. 3
10. S. Huang, R. Jin, and Z. Zhou. Active Learning by Querying Informative and Representative Examples. In NIPS, 2010. 2
11. P. Jain and A. Kapoor. Active learning for large multi-class problems. In CVPR, 2009. 2
12. A. J. Joshi, F. Porikli, and N. Papanikolopoulos. Multi-class active learning for image classification. In CVPR, 2009. 2, 3
13. B. Leibe and B. Schiele. Analyzing Appearance and Contour Based Methods for Object Categorization. In CVPR, 2003. 3
14. H. T. Nguyen and A. Smeulders. Active learning using preclustering. In ICML, 2004. 2
15. T. Osugi and S. Scott. Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning. In ICDM, 2005. 1, 2, 3, 6, 7
16. G. Schohn and D. Cohn. Less is more: Active learning with support vector machines. ICML, 2000. 2
17. B. Settles and M. Craven. An analysis of active learning strategies for sequence labeling tasks. In EMNLP, 2008. 1, 2
18. S. B. Thrun and K. Moeller. Active Exploration in Dynamic Environments. In NIPS, 1992. 2
19. S. Tong and D. Koller. Support Vector Machine Active Learning with Applications to Text Classification. JMLR, pages 45-66, 2001. 2
20. S. Vijayanarasimhan and K. Grauman. Large-Scale Live Active Learning : Training Object Detectors with Crawled Data and Crowds. In CVPR, 2011. 2
21. R. Yan, J. Yang, and A. Hauptmann. Automatically labeling video data using multi-class active learning. In ICCV, 2003. 2, 7
22. L. Zhang, C. Chen, J. Bu, D. Cai, X. He, and T. S. Huang. Active Learning based on Locally Linear Reconstruction. PAMI, 6(1), 2007. 2
23. B. Zhao, F. Wang, C. Zhang, and Y. Song. Active model selection for graph-based semi-supervised learning. In ICASSP, 2008. 2
24. D. Zhou, O. Bousquet, and T. Lal. Learning with local and global consistency. In NIPS, 2004. 3
25. X. Zhu, J. Lafferty, and Z. Ghahramani. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions. In ICML, WS, 2003. 2