Indoor location estimation with reduced calibration exploiting unlabeled data via hybrid generative/discriminative learning

IEEE Transactions on Mobile Computing

Volumn 11, Issue 11, 2012, Pages 1613-1626

  Ouyang, Robin Wentao ^a   Wong, Albert Kai Sun ^a   Lea, Chin Tau ^a   Chiang, Mung ^b  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b PRINCETON UNIVERSITY   (United States)

Author keywords

expectation maximization; fisher kernel; hybrid semi supervised learning; Indoor location estimation; least square support vector machine; naive Bayes; wireless local area network

Indexed keywords

EXPECTATION MAXIMIZATION; FISHER KERNELS; INDOOR LOCATIONS; LEAST SQUARE SUPPORT VECTOR MACHINES; NAIVE BAYES; SEMI-SUPERVISED LEARNING;

ESTIMATION; LEARNING ALGORITHMS; SUPERVISED LEARNING; WIRELESS LOCAL AREA NETWORKS (WLAN);

CALIBRATION;

EID: 84866675729     PISSN: 15361233     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMC.2011.193     Document Type: Article

References (37)

1. M. Rodriguez, J. Favela, E. Martinez, and M. Munoz, "Location-Aware Access to Hospital Information and Services," IEEE Trans. Information Technology in Biomedicine, vol. 8, no. 4, pp. 448-455, Dec. 2004.
2. H. Harroud, M. Ahmed, and A. Karmouch, "Policy-Driven Personalized Multimedia Services for Mobile Users," IEEE Trans. Mobile Computing, vol. 2, no. 1, pp. 16-24, Jan.-Mar. 2003.
3. C. Patterson, R. Muntz, and C. Pancake, "Challenges in Location-Aware Computing," IEEE Pervasive Computing, vol. 2, no. 2 pp. 80-89, Apr.-June 2003.
4. A.K.-S. Wong, T.K. Woo, A.-L. Lee, X. Xiao, V.-H. Luk, and K.W. Cheng, "An AGPS-Based Elderly Tracking System," Proc. First Int'l Conf. Ubiquitous and Future Networks (ICUFN '09), pp. 100-105, June 2009.
5. P. Bahl and V. Padmanabhan, "RADAR: An In-Building RF-Based User Location and Tracking System," Proc. IEEE INFOCOM, vol. 2, pp. 775-784, 2002.
6. J. Pan, J. Kwok, Q. Yang, and Y. Chen, "Multidimensional Vector Regression for Accurate and Low-Cost Location Estimation in Pervasive Computing," IEEE Trans. Knowledge and Data Eng., vol. 18, no. 3, pp. 1181-1193, Sept. 2006.
7. A. Kushki, K. Plataniotis, and A. Venetsanopoulos, "Kernel-Based Positioning in Wireless Local Area Networks," IEEE Trans. Mobile Computing, vol. 6, no. 6, pp. 689-705, June 2007.
8. T. Roos, P. Myllymäki, H. Tirri, P. Misikangas, and J. Sievänen, "A Probabilistic Approach to WLAN User Location Estimation," Int'l J. Wireless Information Networks, vol. 9, no. 3, pp. 155-164, 2002.
9. Z. Wu, C. Li, J. Ng, and K. Leung, "Location Estimation via Support Vector Regression," IEEE Trans. Mobile Computing, vol. 6, no. 3, pp. 311-321, Mar. 2007.
10. Y. Chen, Q. Yang, J. Yin, and X. Chai, "Power-Efficient Access-Point Selection for Indoor Location Estimation," IEEE Trans. Knowledge and Data Eng., vol. 18, no. 7, pp. 877-888, July 2006.
11. R.W. Ouyang, A.K. Wong, and C.T. Lea, "Received Signal Strength-Based Wireless Localization via Semidefinite Programming: Noncooperative and Cooperative Schemes," IEEE Trans. Vehicular Technology, vol. 59, no. 3, pp. 1307-1318, Mar. 2010.
12. X. Li and K. Pahlavan, "Super-Resolution TOA Estimation with Diversity for Indoor Geolocation," IEEE Trans. Wireless Comm., vol. 3, no. 1, pp. 224-234, Jan. 2004.
13. C. Yang, Y. Huang, and X. Zhu, "Hybrid TDOA/AOA Method for Indoor Positioning Systems," Proc. Institution of Eng. and Technology Seminar Location Technologies, pp. 1-5, 2008.
14. M. Kjærgaard, "A Taxonomy for Radio Location Fingerprinting," Proc. Int'l Conf. Location and Context-Awareness, pp. 139-156, 2007.
15. C. Bishop et al., Pattern Recognition and Machine Learning. Springer, 2006.
16. E. Alpaydin, Introduction to Machine Learning, second ed. MIT Press, 2010.
17. A. Jordan, "On Discriminative vs. Generative Classifiers: A Comparison of Logistic Regression and Naive Bayes," Proc. Conf. Advances in Neural Information Processing Systems, vol. 2, pp. 841-848, 2002.
18. A. Dempster, N. Laird, and D. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc. Series B (Methodological), vol. 39, no. 1, pp. 1-38, 1977.
19. T. Jaakkola and D. Haussler, "Exploiting Generative Models in Discriminative Classifiers," Proc. Advances in Neural Information Processing Systems, pp. 487-493, 1999.
20. J. Suykens and J. Vandewalle, "Least Squares Support Vector Machine Classifiers," Neural Processing Letters, vol. 9, no. 3, pp. 293-300, 1999.
21. M. Youssef et al., "WLAN Location Determination via Clustering and Probability Distributions," Proc. First IEEE Int'l Conf. Pervasive Computing and Comm. (PerCom '03), pp. 143-150, 2003.
22. M. Brunato et al., "Transparent Location Fingerprinting for Wireless Services," Proc. Med-Hoc-Net, vol. 2002, 2002.
23. J. Krumm and J. Platt, "Minimizing Calibration Effort for an Indoor 802.11 Device Location Measurement System," Microsoft Research, Nov. 2003.
24. X. Chai and Q. Yang, "Reducing the Calibration Effort for Probabilistic Indoor Location Estimation," IEEE Trans. Mobile Computing, vol. 6, no. 6, pp. 649-662, June 2007.
25. D. Madigan, E. Einahrawy, R. Martin, W. Ju, P. Krishnan, and A. Krishnakumar, "Bayesian Indoor Positioning Systems," Proc. IEEE INFOCOM, vol. 2, pp. 1217-1227, 2005.
26. S. Liu, H. Luo, and S. Zou, "A Low-Cost and Accurate Indoor Localization Algorithm Using Label Propagation Based Semi-Supervised Learning," Proc. Fifth Int'l Conf. Mobile Ad-Hoc and Sensor Networks, pp. 108-111, 2009.
27. X. Zhu and Z. Ghahramani, "Learning from Labeled and Unlabeled Data with Label Propagation," Technical Report CMUCALD-02-107, School of Computer Sciences, Carnegie Mellon Univ., 2002.
28. S. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice-Hall, 1993.
29. H. Hashemi, "The Indoor Radio Propagation Channel," Proc. IEEE, vol. 81, no. 7, pp. 943-968, July 2002.
30. R.W. Ouyang, A. Wong, and K. Woo, "Indoor Localization via Discriminatively Regularized Least Square Classification," Int'l J. Wireless Information Networks, vol. 18, pp. 57-72, http://dx.doi.org/10.1007/ s10776-011-0133-5, 2011.
31. T.M. Mitchell, "Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression," Machine Learning, McGraw Hill, 2005.
32. T. Roos, P. Myllymaki, and H. Tirri, "A Statistical Modeling Approach to Location Estimation," IEEE Trans. Mobile Computing, vol. 1, no. 1, pp. 59-69, Jan.-Mar. 2002.
33. K. Nigam, A. McCallum, S. Thrun, and T. Mitchell, "Text Classification from Labeled and Unlabeled Documents Using EM," Machine Learning, vol. 39, no. 2, pp. 103-134, 2000.
34. T. Hofmann, "Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization," Proc. Neural Information Processing Systems, 2000.
35. J. Ye and T. Xiong, "SVM Versus Least Squares SVM," Proc. Int'l Conf. Artificial Intelligence and Statistics, pp. 640-647, 2007.
36. B. Schölkopf and A. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, 2002.
37. K. Pahlavan and A. Levesque, Wireless Information Networks. Wiley, 1995.