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WiFi - guided visual loop closure for indoor navigation using mobile devices

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Języki publikacji
EN
Abstrakty
EN
Mobile, personal devices are getting more capable every year. Equipped with advanced sensors, mobile devices can use them as a viable platform to implement and test more complex algorithms. This paper presents an energy-efficient person localization system allowing to detect already visited places. The presented approach combines two independent information sources: wireless WiFi adapter and camera. The resulting system achieves higher recognition rates than either of the separate approaches used alone. The evaluation of presented system is performed on three datasets recorded in buildings of different structure using a modern Android device.
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  • Institute of Control and Information Engineering, Poznań University of Technology, Poznań, Poland
Bibliografia
  • [1] P. Bahl, V. N. Padmanabhan, “RADAR: An In-Building RF-Based User Location and Tracking System.” In: 19th Annual Joint Conf. of the IEEE 17 Journal of Automation, Mobile Robotics & Intelligent Systems VOLUME 8, N◦ 3 2014 Computer and Communications Societies (INFOCOM), 2000, pp. 775–784. DOI: http://dx.doi.org/10.1109/INFCOM.2000.832252.
  • [2] H. Bay, A. Ess, T. Tuytelaars, L. Van Gool, “SURF:Speeded up robust features”, Comp. Vis. and Image Underst., vol. 110, no. 3, 2008, pp. 346–359.DOI: http://dx.doi.org/10.1016/j.cviu.2007.09.014.
  • [3] J. Biswas, M. Veloso, “WiFi localization and navigation for autonomous indoor mobile robots.” In: 10 IEEE Int. Conf. on Robotics and Automation (ICRA), 20, 2010, pp. 4379–4384. DOI: http://dx.doi.org/10.1109/ROBOT.2010.5509842.
  • [4] S. Boonsriwai, A. Apavatjrut, “Indoor WIFI localization on mobile devices.” In: 2013 10th Int. Conf. on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013, pp. 1–5. DOI: http://dx.doi.org/10.1109/ECTICon.2013.6559592.
  • [5] G. Bradski, “The OpenCV library”, Dr. Dobb’s Journal of Software Tools, opencv.org, 2000.
  • [6] G. Csurka et al., “Visual categorization with bags of keypoints.” In: Workshop on Statistical Learning in Computer Vision, ECCV, 2004, pp. 1–22.
  • [7] N. Dalal, B. Triggs, “Histograms of oriented gradients for human detection.” In: IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), 2005, vol. 1, pp. 886–893. DOI:10.1109/CVPR.2005.177.
  • [8] T. Gallagher et al., “Indoor positioning system based on sensor fusion for the Blind and Visually Impaired.” In: Int. Conf. Inndoor Positioning and Indoor Navigation (IPIN), 2012, pp. 1–9. DOI:10.1109/IPIN.2012.6418882.
  • [9] A. Glover et al., “OpenFABMAP: An Open Source Toolbox for Appearance-based Loop Closure Detection.” In: IEEE Int. Conf. on Robotics and Automation, St Paul, Minnesota, 2011.
  • [10] J. Gośliński, M. Nowicki, “Performance Comparison of EKF-based Algorithms for Orientation Estimation on Android Platform.”
  • [11] M. Holĉik, “Indoor Navigation for Android,” M.S. thesis, Faculy of Informatics, Masaryk Univ., Brno, 2012.
  • [12] H. Liu et al., “Accurate WiFi Based Localization for Smartphones Using Peer Assistance,” IEEE Transactions on Mobile Computing, vol. PP, no. 99, 2013, pp. 1. DOI: 10.1109/TMC.2013.140.
  • [13] K. Muzzammil bin Saipullah, A. Anuar, N. A. binti Ismail, Y. Soo, “Real-time video processing using ative programming on Android platform.”In: Proc. IEEE 8th Int. Col. on Signal Proc. and its App., 2012, pp. 276–281.
  • [14] M. Nowicki, P. Skrzypczyński, “Combining photometric and depth data for lightweight and robust visual odometry.” In: European Conference on Mobile Robots (ECMR), 2013, pp. 125–130.DOI: 10.1109/ECMR.2013.6698831.
  • [15] M. Nowicki, P. Skrzypczynski, “Performance Comparison of Point Feature Detectors and Descriptors for Visual Navigation on Android Platform,” Int. Wireless Communications and Mobile Computing Conference (IWCMC), 2014.
  • [16] K. Pulli et al., “Real-time Computer Vision with OpenCV,” Commun. ACM, 2012, vol. 55, no. 6, pp. 61–69. DOI: 0.1145/2184319.2184337.
  • [17] N. Ravi, P. Shankar, A. Frankel, A. Elgammal, L. Iftode, “Indoor localization using camera phones,” Proc. 7th IEEE Work. on Mobile Comp. Sys. and App., 2006, pp. 1–7.
  • [18] U. Shala, A. Rodriguez, “Indoor Positioning using Sensor-fusion in Android Devices,” M.S. Thesis, Dept. Computer Science, Kristianstad Univ., Kristianstad, 2011. http://hkr.diva-portal.org/smash/record.jsf?pid=diva2:475619
  • [19] M. Quigley, D. Stavens, A. Coates, S. Thrun,“Sub-meter indoor localization in unmodified environments with inexpensive sensors.” Proc. IEEE/RSJ Int. Conf. on IROS, Taipei, 2010, pp. 2039–2046. DOI:10.1109/IROS.2010.5651783.
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