Multi-metric learning for multi-sensor fusion based classification

Information Fusion

Volumn 14, Issue 4, 2013, Pages 431-440

  Zhang, Yanning ^a   Zhang, Haichao ^a,b   Nasrabadi, Nasser M ^c   Huang, Thomas S ^b  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c U S ARMY RESEARCH LABORATORY   (United States)

Author keywords

Joint classification; Metric learning; Multi sensor fusion

Indexed keywords

INFORMATION FUSION; SOFTWARE ENGINEERING;

EUCLIDEAN METRICS; HETEROGENOUS SENSORS; KERNEL MAPPING; METRIC LEARNING; MULTI-SENSOR DATA; MULTI-SENSOR FUSION; MULTIPLE SENSORS; UNIFIED OPTIMIZATION FRAMEWORK;

LEARNING ALGORITHMS;

EID: 84887818232     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.inffus.2012.05.002     Document Type: Article

References (32)

1. C.-C. Shen, W.-H. Tsai, Multisensor fusion in smartphones for lifestyle monitoring, in: International Conference on Body Sensor Networks, 2010, pp. 36-43.
2. A. Fleury, M. Vacher, N. Noury, SVM-based multi-modal classification of activities of daily living in health smart homes: sensors, algorithms and first experimental results, IEEE Transactions on Information Technology in Biomedicine 14 (2) (2010) 274-283.
3. E. Zervas, A. Mpimpoudis, C. Anagnostopoulos, O. Sekkas, S. Hadjiefthymiades, Multisensor data fusion for fire detection, Information Fusion 12 (2011) 150-159.
4. M. Kushwaha, X. Koutsoukos, Collaborative target tracking using multiple visual features in smart camera networks, in: International Conference on Information Fusion, 2010, pp. 1-8.
5. M.A. Davenport, C. Hegde, M.F. Duarte, R.G. Baraniuk, Joint manioflds for data fusion, IEEE Transactions on Image Processing 19 (10) (2010) 2580-2594.
6. C. Meesookho, S. Narayanan, C. Raghavendra, Collaborative classification applications in sensor networks, in: Sensor Array and Multichannel Signal Processing Workshop, 2002, pp. 370-374.
7. X.R. Li, Y. Zhu, C. Han, Optimal linear estimation fusion - part I: unified fusion rules, Journal of Dynamic Systems, Measurement, and Control 49 (9) (2003) 2192-2208.
8. K.R. Varshney, A.S. Willsky, Linear dimensionality reduction for margin-based classification: high-dimensional data and sensor networks, IEEE Transactions on Signal Processing 59 (6) (2011) 2496-2512.
9. S. Lee, V. Shin, Computationally efficient multisensor fusion estimation algorithms, Journal of Dynamic Systems, Measurement, and Control 132 (2) (2010). 024503-1-024503-2.
10. H.M. El-Bakry, An efficient algorithm for pattern detection using combined classifiers and data fusion, Information Fusion 11 (2010) 133-148.
11. N. Garcia-Pedrajas, D. Ortiz-Boyer, An empirical study of binary classifier fusion methods for multiclass classification, Information Fusion 12 (2011) 110-130.
12. T. Cover, P. Hart, Nearest neighbor pattern classification, IEEE Transactions on Information Theory 13 (1) (1967) 21-27.
13. J.V. Davis, B. Kulis, P. Jain, S. Sra, I.S. Dhillon, Information- theoretic metric learning, in: International Conference on Machine Learning, 2007, pp. 209-216.
14. Z. Lu, P. Jain, I.S. Dhillon, Geometry aware metric learning, in: International Conference on Machine Learning, 2009.
15. K.Q. Weinberger, L.K. Saul, Distance metric learning for large margin nearest neighbor classification, Journal of Machine Learning Research 10 (2009) 207-244.
16. H. Zhang, N.M. Nasrabadi, T.S. Huang, Y. Zhang, Heterogenous multi-metric learning for multi-sensor fusion, in: International Conference on Information Fusion, 2011, pp. 1-8.
17. I. Joliffe, Principal Component Analysis, Springer-Verlag, New York, 1986.
18. A. Martinez, A. Kak, PCA versus LDA, IEEE Transactions on Pattern Analysis and Machine Intelligence 23 (2) (2001) 228-233.
19. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, S. Lin, Graph embedding and extensions: a general graph framework for dimensionality reduction, IEEE Transactions on Pattern Analysis and Machine Intelligence 29 (1) (2007) 40-51.
20. L. Yang, R. Jin, L.B. Mummert, R. Sukthankar, A. Goode, B. Zheng, S.C.H. Hoi, M. Satyanarayanan, A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (1) (2010) 30-44.
21. S.C.H. Hoi, W. Liu, S.-F. Chang, Semi-supervised distance metric learning for collaborative image retrieval and clustering, ACM Transactions on Multimedia Computing, Communications and Applications 6 (3).
22. L. Si, R. Jin, S.C.H. Hoi, M.R. Lyu, Collaborative image retrieval via regularized metric learning, Multimedia Systems 12 (1) (2006) 34-44.
23. S.C.H. Hoi, W. Liu, M.R. Lyu, W.-Y. Ma, Learning distance metrics with contextual constraints for image retrieval, in: IEEE Conference on Computer Vision and Patern Recognition (CVPR), 2006, pp. 2072-2078.
24. S. Sun, Local within-class accuracies for weighting individual outputs in multiple classifier systems, Pattern Recognition Letters 31 (2) (2010) 119-124.
25. S. Sun, Q. Chen, Hierarchical distance metric learning for large margin nearest neighbor classification, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI) 25 (7) (2011) 1073-1087.
26. S. Parameswaran, K.Q. Weinberger, Large margin multi-task metric learning, in: Advances in Neural Information Processing Systems, 2010, pp. 1867-1875.
27. L. Torresani, K. chih Lee, Large margin component analysis, in: Advances in Neural Information Processing Systems, 2007, pp. 1385-1392.
28. V. Mirelli, S. Tenney, Y. Bengio, N. Chapados, O. Delalleau, Statistical machine learning algorithms for target classification from acoustic signature, in: Proceedings of MSS Battlespace Acoustic and Magnetic Sensors, 2009.
29. S. Engelberg, E. Tadmor, Recovery of edges from spectral data with noise-a new perspective, SIAM Journal on Numerical Analysis 46 (5) (2008) 2620-2635.
30. D.G. Childers, D.P. Skinner, R.C. Kemerait, The Cepstrum: a guide to processing, Proceedings of IEEE 65 (1977) 1428-1443.
31. C.M. Bishop, Pattern Recognition and Machine Learning, Springer, New York, 2006.
32. P. Tseng, S. Yun, A coordinated gradient descent method for nonsmooth separable minimizatin, Mathematical Programming 117 (2009) 387-423.