Image Based Navigation System for Pedestrians in an Indoor Environment

Authors

  • Kazeem Oyebode Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa.
  • Shengzhi Du Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa.
  • Barend Jacobus van Wyk Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa.
  • Karim Djouani Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa.

Keywords:

Image Localization, Image Matching, Image Processing, Pedestrian Navigation,

Abstract

Indoor navigation systems provide means to guide pedestrians to their various destinations. While many tools that take advantage of the Global Positioning System (GPS) for outdoor navigation exists, their usefulness is limited to the availability of GPS signal reception, which is usually poor in indoor environments. In this research, we propose a method that employs only images for indoor pedestrian navigation. In the proposed method, a map of the indoor environment is first transformed into a graph model where features of indoor environment are attached to graph nodes and their distances represented by the graph edges. Feature images of initial and destination locations are provided by the pedestrian who needs to be guided. These images are fed into the created graph model and thereafter the Speeded-Up Robust Features (SURF) is then used to find a match to these images to discover their corresponding graph nodes. Graph nodes are identified in a manner that corresponds to pedestrian localized position and destination. Leveraging on these nodes in the graph, models are proposed to find the shortest path to user’s destination with instructions and graphical navigation path to enhance maneuverability. Experiment carried out on an indoor environment of the French South African Institute of Technology building, (Tshwane University of Technology) shows encouraging results.

References

H. Aoki, 8. Schiele and A. Pentland, "Realtime personal positioning system for wearable computers," in ISWC, Proceedings of the 3 rd IEEE International Symposium on Wearable Computers , 1999.

D. Robertson and R. Cipolla, "An image-based system for urban navigation"," in Proceedings of British Machine Vision Conference, 2004.

H. Hile and G. Borriello, "Information overlay for camera phones in indoor environments," in 3rd International Symposium on Locationand Context Awareness, Lecture Notes in Computer Science, 2007.

C. Keßler, C. Ascher, M. Flad, and G. F. Trommer, Gyroscopy and Navigation, vol. 3, no. 2, p. 79–90, 2012.

F. Hartmann, D. Rifat and W. Stork, "Hybrid Indoor Pedestrian Navigation Combining an INS and a Spatial Non-Uniform UWBnetwork," in 19th International Conference on Information Fusion, Heidelberg, 2016.

M. Placer and Stanislav Kovačič, "Enhancing Indoor Inertial Pedestrian Navigation Using a Shoe-Worn Marker," Sensors, vol. 13, pp. 9837-9859, 2013.

R. Nitami, A. Suzuki and Yoshitoshi Murata, "Development of a Pedestrian Navigation System Without Additional Infrastructures," in 2014 International Conference on Indoor Positioning and Indoor Navigation, 2014.

"SKYCAL," MIT, [Online]. Available: http://senseable.mit.edu/skycall/. [Accessed 2 2 2017].

W. Elloumi ; K. Guissous ; A. Chetouani ; R. Canals ; R. Leconge ; B. Emile ; S. Treuillet, "Indoor navigation assistance with a Smartphone camera based on vanishing points," in "Indoor navigation assistance with a Smartphone camera based on vanishing points," International Conference on Indoor Positioning and Indoor Navigation, Montbeliard-Belfort, 2013.

W. Zhang and J. Kosecka, "Image Based Localization in Urban Environments," in Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06), 2006.

E. Y. Kim, "Wheelchair Navigation System for Disabled and Elderly People," Sensors, vol. 16, no. 11, 2016.

S. Lynen, M. Bosse and R. Siegwart, "Trajectory-Based PlaceRecognition for Efficient Large Scale Localization," Int J Comput Vis , vol. 124, pp. 49-62, 2017.

H. Peng, F. Long and Z. Chi, "Document Image Recognition based on template matching of component block projections,," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1188-1192, 2003.

Q. I. Pham, R. Jalovecký and M. Polášek, "Using template matching for object recognition in infrared video sequences," in IEEE/AIAA 34th Digital Avionics Systems Conference (DASC), Prague, 2015.

Z. Yang, "Fast Template Matching Based on Normalized Cross Correlation with Centroid Bounding," in International Conference on Measuring Technology and Mechatronics Automation, Changsha, 2010.

H. Bay, A. Ess, T. Tuytelaars, and Luc Van Gool, "Speeded-Up Robust Features (SURF)," Computer Vision and Image Understanding, vol. 110, no. 3, pp. 346-359 , 2008.

M. Trajkovic,. and M. Hedley., "1998. FAST corner detector," Image and Vision Computing, vol. 16:, pp. 75-87, 1998.

A. Satpathy, X. Jiang and H. L. Eng, "LBP-Based Edge-Texture Features for Object Recognition," IEEE Transactions on Image Processing, vol. 23, no. 5, pp. 1953-1964, 2014.

L. Ruotsalainen, H. Kuusniemi and R. Chen,, "Overview of methods for visual-aided pedestrian navigation," in Ubiquitous Positioning Indoor Navigation and Location Based Service, , Kirkkonummi, 2010.

F. Boniardi, A. Valada, Wolfram Burgard, Gian Diego Tipaldi, "Autonomous Indoor Robot Navigation Using a Sketch Interface for Drawing Maps and Routes," in IEEE International Conference on Robotics and Automation (ICRA), Sweden, 2016.

H. Bay., A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-up robust features (SURF)," Lecture Notes in Computer Science, vol. 3951, pp. 404-417., 2006.

J. Lu and C. Dong,, "Research of shortest path algorithm based on the data structure," in International Conference on Computer Science and Automation Engineering, Beijing, 2012.

K.O Oyebode, S. Du, B.J. van Wyk, and K Djouani,, "Dataset," 18 January 2018. [Online]. Available: https://drive.google.com/open?id=17BIoUzeE6yLycwn2HVqas8O9I0 _HelbI. [Accessed 26 March 2018].

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Published

2020-06-29

How to Cite

Oyebode, K., Du, S., Jacobus van Wyk, B., & Djouani, K. (2020). Image Based Navigation System for Pedestrians in an Indoor Environment. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 12(2), 45–51. Retrieved from https://jtec.utem.edu.my/jtec/article/view/5205

Issue

Vol. 12 No. 2: April - June 2020

Section

Articles

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