Skip to main content
SpringerLink
Log in

Performance Evaluation of Spatial Correlation-based Feature Detection and Matching for Automated Wheelchair Navigation System

  • Published:
International Journal of Intelligent Transportation Systems Research Aims and scope Submit manuscript

Abstract

A wheelchair navigation system have emerged in response to high demand for mobile location-aware applications. Nevertheless, single localization technology have several limitations and vulnerabilities; to provide a universal localization solution for various environment. In this paper, we present our new new feature detection and matching algorithm approach for automated wheelchair navigation system. This kind approach is using multi localization solution, which are; Wireless LAN and camera. Thus, these location information are combined by model fitting in order to find the absolute of user target position. As a finding, our experimental results indicate positioning accuracy of 0–6 m with a 23 % trial by given five (5) different locations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  1. R. Ivanov, “RSNAVI: an RFID-based context-aware indoor navigation system for the blind,” in Proceedings of the 13th International Conference on Computer Systems and Technologies, New York, NY, USA, 2012, pp. 313–320.

  2. Esposito, C., Ficco, M.: Deployment of RSS-based indoor positioning systems. Int. J. Wirel. Inf. Networks 18(4), 224–242 (2011)

    Article  Google Scholar 

  3. Lee, B.-G., Chung, W.-Y.: Multitarget three-dimensional indoor navigation on a PDA in a wireless sensor network. Ieee Sensors J. 11(3), 799–807 (2011)

    Article  MathSciNet  Google Scholar 

  4. Liao, L., Lin, K., Wang, X., Lai, X., Vuong, S.T.: WiFi positioning overview. Int. J. Commun. Networks Distrib. Syst. 7(3), 229–248 (2011)

    Article  Google Scholar 

  5. Giorgetti, G., Farley, R., Chikkappa, K., Ellis, J., Kaleas, T.: Cortina: collaborative indoor positioning using low-power sensor networks. J. Locat. Based Serv. 6(3), 137–160 (2012)

    Article  Google Scholar 

  6. C.-P. Yen and P. J. Voltz, “Indoor positioning based on statistical multipath channel modeling,” Eurasip J. Wirel. Commun. Netw., vol. 2011, no. 1, p. 189, 2011.

  7. Lu, M.: A framework for indoor construction resources tracking by applying wireless sensor networks. Can. J. Civ. Eng. 39(9), 1083–1088 (2012)

    Article  Google Scholar 

  8. Shen, X., Lu, M.: A framework for indoor construction resources tracking by applying wireless sensor networks 1 1 This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management. Can. J. Civ. Eng. 39(9), 1083–1088 (2012)

    Article  Google Scholar 

  9. M. Nicoli, S. Gezici, Z. Sahinoglu, and H. Wymeersch, “Localization in mobile wireless and sensor networks,” Eurasip J. Wirel. Commun. Netw., vol. 2011, no. 1, p. 197, 2011.

  10. C. Mensing, S. Sand, and A. Dammann, “Hybrid data fusion and tracking for positioning with GNSS and 3GPP-LTE,” Int. J. Navig. Obs., vol. 2010, 2010.

  11. Liew, S.C., Tan, K.G., Tan, C.P.: Non-Taylor series based positioning method for hybrid GPS/Cellphone system. J. Electromagn. Waves Appl. 20(6), 717–729 (2006)

    Article  Google Scholar 

  12. Liew, S.C., Tan, K.G., Lim, T.S.: Investigation of direct A-GPS positioning for hybrid E-OTD/GNSS. J. Electromagn. Waves Appl. 20(1), 79–87 (2006)

    Article  Google Scholar 

  13. Yang, H., Park, K., Lee, J.G., Chung, H.: A rotating sonar and a differential encoder data fusion for map-based dynamic positioning. J Intell Robot. Syst 29(3), 211–232 (2000)

    Article  MATH  Google Scholar 

  14. Shoval, S., Zeitoun, I., Lenz, E.: Implementation of a Kalman filter in positioning for autonomous vehicles, and its sensitivity to the process parameters. Int. J. Adv. Manuf. Technol. 13(10), 738–746 (1997)

    Article  Google Scholar 

  15. Yost, M.G., Gadgil, A.J., Drescher, A.C., Zhou, Y., Simonds, M.A., Levine, S.P., Nazaroff, W.W., Saisan, P.A.: Imaging indoor tracer-gas concentrations with computed tomography: experimental results with a remote sensing FTIR system. Am. Ind. Hyg. Assoc. J. 55(5), 395–402 (1994)

    Article  Google Scholar 

  16. Cao, Z.L., Oh, S.J., Hall, E.L.: Dynamic omnidirectional vision for mobile robots. J. Robot. Syst. 3(1), 5–17 (1986)

    Article  Google Scholar 

  17. A. Kosaka and J. Pan, “Purdue Experiments in Model-Based Vision for Hallway Navigation,” in In Proceedings of the Workshop on Vision for Robots in IROS’95, 1995, pp. 87–96.

  18. N. Karlsson, E. di Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M. E. Munich, “The vSLAM Algorithm for Robust Localization and Mapping,” in Proceedings of the 2005 I.E. International Conference on Robotics and Automation, 2005. ICRA 2005, 2005, pp. 24–29.

  19. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3D. Acm Trans Graph 25(3), 835–846 (2006)

    Article  Google Scholar 

  20. Hile, H., Borriello, G.: Positioning and orientation in indoor environments using camera phones. Ieee Comput. Graph. Appl. 28(4), 32–39 (2008)

    Article  Google Scholar 

  21. T. Ruiz-López, J. L. Garrido, K. Benghazi, and L. Chung, “A Survey on Indoor Positioning Systems: Foreseeing a Quality Design,” in Distributed Computing and Artificial Intelligence, vol. 79, A. P. Leon F. de Carvalho, S. Rodríguez-González, J. F. Paz Santana, and J. M. C. Rodríguez, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 373–380.

  22. Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M., Rosly, M.A.: Investigation of color constancy for ubiquitous wireless LAN/Camera positioning: an initial outcome. Int. J. Adv. Comput. Technol. 4(7), 269–280 (2012)

    Article  Google Scholar 

  23. Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M.: Ubiquitous positioning: a taxonomy for location determination on mobile navigation system. Signal Image Process. Int. J. 2(1), 24–34 (2011)

    Article  Google Scholar 

  24. W. M. Y. W. Bejuri, M. M. Mohamad, M. Sapri, and M. A. Rosly, “Ubiquitous WLAN/Camera Positioning using Inverse Intensity Chromaticity Space-based Feature Detection and Matching: A Preliminary Result,” in International Conference on Man–machine Systems 2012, Penang, Malaysia.

  25. A. Chakrabarti, K. Hirakawa, and T. Zickler, “Computational color constancy with spatial correlations,” Harv. Sch. Eng. Appl. Sci. Tr-09-10, 2010.

  26. P. Bahl and V. N. Padmanabhan, “RADAR: An in-building RF-based user location and tracking system,” in INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, 2000, vol. 2, pp. 775–784.

  27. D. Wettschereck, T. G. Dietterich, and R. Sutton, “An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms,” in Machine Learning, 1995, pp. 5–28.

  28. D. Comaniciu and P. Meer, “Mean shift analysis and applications,” in The Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999, 1999, vol. 2, pp. 1197–1203 vol.2.

  29. D. S. Guru, R. Dinesh, and P. Nagabhushan, “Boundary based corner detection and localization using new ‘cornerity’ index: a robust approach,” in First Canadian Conference on Computer and Robot Vision, 2004. Proceedings, 2004, pp. 417–423.

Download references

Acknowledgement

This work has been funded by the Research University Grant (RUG) under project no. Q.130000.2628.08J05

Author information

Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Wan Mohd Yaakob Wan Bejuri, Mohd Murtadha Mohamad & Mohd Shafry Mohd Rahim

  2. Centre of Real Estate Studies, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Maimunah Sapri

  3. Department of Computer Science and Engineering, Qatar University, Doha, Qatar

    Junaid Ahsenali Chaudry

Authors
  1. Wan Mohd Yaakob Wan Bejuri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohd Murtadha Mohamad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maimunah Sapri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohd Shafry Mohd Rahim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Junaid Ahsenali Chaudry
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wan Mohd Yaakob Wan Bejuri.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M. et al. Performance Evaluation of Spatial Correlation-based Feature Detection and Matching for Automated Wheelchair Navigation System. Int. J. ITS Res. 12, 9–19 (2014). https://doi.org/10.1007/s13177-013-0064-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13177-013-0064-x

Keywords

Search

Navigation