Adaptive pedestrian activity classification for indoor dead reckoning systems

2013 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2013

Volumn , Issue , 2013, Pages

  Khalifa, Sara ^a,b   Hassan, Mahbub ^a,b   Seneviratne, Aruna ^a,b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b CSIRO   (Australia)

Author keywords

Indoor Localization; Pedestrian Activity Classification; Pedestrian Dead Reckoning

Indexed keywords

COMPUTATIONAL COMPLEXITY; MOBILE DEVICES;

ACTIVITY CLASSIFICATIONS; BUILDING FACILITIES; CLASSIFICATION ACCURACY; DEAD RECKONING SYSTEM; INDOOR LOCALIZATION; PEDESTRIAN DEAD RECKONING SYSTEMS; PEDESTRIAN DEAD RECKONINGS; RESOURCE CONSTRAINT;

NAVIGATION;

EID: 84900018702     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPIN.2013.6817868     Document Type: Conference Paper

References (16)

1. O. Mezentsev, G. Lachapelle, and J. Colin, "Pedestrian dead reckoning - a solution to navigation in gps signal degraded areas," Geomatica, vol. 59, no. 2, pp. 175-182, 2005.
2. N. Kothari, B. Kannan, and M. B. Dias, "Robust indoor localization on a commercial smart-phone," in Technical Report CMU-RI-TR-11-27, Robotics Institute, Carnegie-Mellon University, Pittsburgh, PA, August, 2011.
3. D. Gusenbauer, C. Isert, and J. Krösche, "Self-contained indoor positioning on off-The-shelf mobile devices," in "International Conference on Indoor Positioning and Indoor Navigation (IPIN10), Zürich, Switzerland, 15-17 Septemper 2010.
4. K. Altun and B. Barshan, "Pedestrian dead reckoning employing simultaneous activity recognition cues," Measurement Science and Technology, vol. 23, no. 2, pp. 1-20, February, 2012.
5. T. Plötz, N. Y. Hammerla, and P. Olivier, "Feature learning for activity recognition in ubiquitous computing," in Proceedings of the Twenty-Second international joint conference on Artificial Intelligence, Barcelona, Catalonia, Spain, 16-22 July 2011.
6. Y.-J. Hong, I.-J. Kim, S. C. Ahn, and H.-G. Kim, "Mobile health monitoring system based on activity recognition using accelerometer," Simulation Modelling Practice and Theory, vol. 18, no. 4, pp. 446-455, 2010.
7. Z. Sun, X. Mao, W. Tian, and X. Zhang, "Activity classification and dead reckoning for pedestrian navigation with wearable sensors," Measurement Science and Technology, vol. 20, no. 1, pp. 1-20, January, 2009.
8. K. Altun, B. Barshan, and O. Tunçel, "Comparative study on classifying human activities with miniature inertial and magnetic sensors," Pattern Recognition, vol. 43, no. 10, pp. 3605-3620, October, 2010.
9. M. Hassan, "A performance model of pedestrian dead reckoning with activity-based location updates," in IEEE International Conference on Networks (ICON), Singapore, 12-14 December, 2012.
10. S. Khalifa and M. Hassan, "Evaluating mismatch probability of activitybased map matching in indoor positioning," in International Conference on Indoor Positioning and Indoor Navigation (IPIN12), Sydney, Australia, 15-17 November 2012.
11. S. Khalifa, M. Hassan, and A. Seneviratne, "Feature selection for floor-changing activity recognition in multi-floor pedestrian navigation," in The Seventh International Conference on Mobile Computing and Ubiquitous Networking (ICMU2014), Singapore, 6-8 January 2014.
12. Z. Yan, V. Subbaraju, D. Chakraborty, A. Misra, and K. Aberer, "Energy-efficient continuous activity recognition on mobile phones: An activity-adaptive approach," in Proceedings of the 16th Annual International Symposium on Wearable Computers (ISWC), Newcastle, UK, 18-22 June 2012.
13. K. Roy, C. Chaudhuri, M. Kundu, M. Nasipuri, and D. K. Basu, "Comparison of the multi layer perceptron and the nearest neighbor classifier for handwritten numeral recognition," Journal of Information Science and Engineering, vol. 21, pp. 1247-1259, 2005.
14. "WEKA Software," http://www.cs.waikato.ac.nz/ml/weka/, accessed on 15 August, 2012.
15. L. Avdiyenko, N. Bertschinger, and J. Jost, "Adaptive sequential feature selection for pattern classification," in Proceedings of the 4th International Conference on Neural Computation Theory and Applications (NCTA 2012), Barcelona, Spain, 5-7 October 2012.
16. "Centro Bankstwon Directory," http://www2.centro.com.au/NR/ rdonlyres/F0D498B9-6E6E-4A49-BB1C-1224AE2047CD/0/SiteMap.pdf, Accessed on 25 July, 2013