Advertisement

Multimedia Tools and Applications

, Volume 73, Issue 3, pp 1597–1615 | Cite as

iNavigation: an image based indoor navigation system

  • E. Wang
  • W. YanEmail author
Article

Abstract

This paper presents a novel image-based indoor navigation web application designed for mobile phone. It is inspired by Google Street View that features 360° imagery for navigation. Ordinary data collection of image based navigation systems implements panorama cameras, so it is difficult to be extended to indoor environment. On the other hand, they cannot provide timely updates because it requires immense image data. This paper introduces a ‘proof of concept’ which only uses ordinary organized photo collections instead of panoramic photo to guide people through the building. It implements SIFT (scale-invariant feature transform) feature detection and ANN (approximately nearest neighbor) search to provide positioning service. People can upload query images to obtain current position. It also enables information sharing by using IPM (inverse perspective mapping) technique to figure out distance from a single query image, and update the query image into the image collection correctly based on the distance calculation.

Keywords

Indoor Navigation Image Photo-based SIFT IPM ANN search Best-bin-first 

References

  1. 1.
    Andoni A, Indyk P (2006) Near-optimal hashing algorithms for near neighbor problem in high dimensions. In Proceedings of the Symposium on Foundations of Computer Science (FOCS‘06)Google Scholar
  2. 2.
    Babbar G, Bajaj P, Chawla A, Gogna M (2010) A comparative study of image matching algorithms. Int J Inf Technol Knowl Manag 2(2):337–339Google Scholar
  3. 3.
    Bahl P, Padmanabhan V (2000) RADAR: an in-building RF-based user location and tracking system. Proc IEEE INFOCOM 2:775–784Google Scholar
  4. 4.
    Beis JS, Lowe DG (1997) Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR), pp 1000–1006Google Scholar
  5. 5.
    Bekkali A, Sanson H, Matsumoto M (2007) RFID indoor positioning based on probabilistic RFID map and kalman filtering. In Proc. of the 3rd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, pp 21–21Google Scholar
  6. 6.
    Bradley D, Brunton A, Fiala M, Roth G (2005) Image-based navigation in real environments using panoramas. In Proc. of IEEE International Workshop on Haptic Audio Visual Environments and their ApplicationsGoogle Scholar
  7. 7.
    Cattenoz M (2011) Indoor navigation 2. In Proc. of Advances in Media Technology, pp 27–34Google Scholar
  8. 8.
    Chum O, Philbin J, Sivic J, Isard M, Zisserman A (2007) Total recall: automatic query expansion with a generative feature model for object retrieval. In Proc. of International Conference on Computer VisionGoogle Scholar
  9. 9.
    Couceiro M (2010) Segmentation, 2010. Available: http://www.mathworks.com/matlabcentral/fileexchange/29517-segmentation
  10. 10.
    Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1:269–271CrossRefzbMATHMathSciNetGoogle Scholar
  11. 11.
    Ekman I, Lankoski P (2002) What should it do? Key issues in navigation interface design for small screen devices. In Proc. of International Conference on Human Factors and Computing Systems, pp 622–623Google Scholar
  12. 12.
    Gezici S, Tian Z, Giannakis GB, Kobayashi H, Molisch AF, Poor HV, Sahinoglu Z (2005) Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks. Proc IEEE Signal Proc Mag 22(4):70–84CrossRefGoogle Scholar
  13. 13.
    Gilliéron P, Merminod B (2003) Personal navigation system for indoor applications. In Proc. of 11th IAIN World Congress, BerlinGoogle Scholar
  14. 14.
    Hess R (2010) An open source SIFT library. ACM MultimediaGoogle Scholar
  15. 15.
    Ishikawa T, Yamazaki T (2009) Showing where to go by maps or pictures: An empirical case study at subway exits. In: Hornsby KS, Claramunt C, Denis M, Ligozat G (eds) Spatial information theory. Springer, Berlin, pp 330–341CrossRefGoogle Scholar
  16. 16.
    Ivanov R (2010) Indoor navigation system for visually impaired. In Proc. Int. Conf. on Computer Systems and Technologies, Sofia, pp 143–149Google Scholar
  17. 17.
    Jaspers H, Schauerte B, Fink GA (2012) SIFT-based camera localization using reference objects for application in multi-camera environments and robotics. In Proc. of International Conference on Pattern Recognition Applications and Methods, PortugalGoogle Scholar
  18. 18.
    Juan L, Gwun O (2009) A comparison of SIFT, PCA-SIFT, and SURF. Int J Image Process (IJIP) 3(4):143–152Google Scholar
  19. 19.
    Kang H, Efros AA, Hebert M, Kanade T (2009) Image matching in large scale indoor environment. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Egocentric Vision, June 2009Google Scholar
  20. 20.
    Karimi H (2011) Indoor navigation. Universal navigation on smartphones. Springer, New York, pp 17–51CrossRefGoogle Scholar
  21. 21.
    Kawaji H, Hatada K, Yamasaki T, Aizawa K (2010) Image-based indoor positioning system: Fast image matching using omnidirectional panoramic images. In Proc. of the 1st ACM International Workshop on Multimodal Pervasive Video Analysis, pp 1–4Google Scholar
  22. 22.
    Ke Y, Sukthankar R (2004) PCA-SIFT: a more distinctive representation for local image descriptors. In Proc. of Conference on Computer Vision and Pattern Recognition, Washington, USA, pp 511–517Google Scholar
  23. 23.
    Kitasuka T, Nakanishi T, Fukuda A (2003) Wireless LAN based indoor positioning system (WiPS) and its simulation. Proc IEEE Pac Rim Conf Commun Comput Signal Proc 1:272–275Google Scholar
  24. 24.
    Kray C, Elting C, Laakso K, Coors V (2003) Presenting route instructions on mobile devices. In Proc. of International Conference on Intelligent User Interfaces, pp 117–124Google Scholar
  25. 25.
    Kray C, Elting C, Laakso K, Coors V (2003) Presenting route instructions on mobile devices. In: Proc. of the 8th International Conference on Intelligent User Interfaces (IUI ‘03), pp 117–124. ACM, New YorkGoogle Scholar
  26. 26.
    Lu Y, Delp E (2004) An overview of problems in image-based location awareness and navigation. In Proc. of Visual Communications and Image Processing, pp 102–109Google Scholar
  27. 27.
    Mallot HA, Biilthoff HH, Little JJ, Bohrer S (1991) Inverse perspective mapping simplifies optical flow computation and obstacle detection. In Biological Cybernetics, pp 177–185Google Scholar
  28. 28.
    Mikolajczyk K, Leibe B, Schiele B (2005) Local features for object class recognition. In Proc. of International Conference on Computer VisionGoogle Scholar
  29. 29.
    Mikolajczyk K, Schmid C (2005) A performance evaluation of local descriptors. IEEE Trans Pattern Anal Mach Learn 27(10):1615–1630CrossRefGoogle Scholar
  30. 30.
    Mikolajczyk K, Tuytelaars T, Schmid C, Zisserman A, Matas J, Schaffalitzky F, Kadir T, Gool LV (2005) A Comparison of Affine Region Detectors. Int J Comput Vis 65(1–2):43–72CrossRefGoogle Scholar
  31. 31.
    Moreels P, Perona P (2005) Evaluation of features detectors and descriptors based on 3D objects. In Proc. of the International Conference on Computer Vision, pp 800–807Google Scholar
  32. 32.
    Morel JM, Yu G (2009) ASIFT: a new framework for fully affine invariant image comparison. SIAM J Imaging Sci 2(2)Google Scholar
  33. 33.
    Muja M, Lowe DG (2009) Fast approximate nearest neighbors with automatic algorithm configuration. In Proc. of International Conference on Computer Vision Theory and Applications (VISAPP), PortugalGoogle Scholar
  34. 34.
    Nene SA, Nayar SK (1997) A simple algorithm for nearest neighbor search in high dimensions. IEEE Trans Pattern Anal Mach Intell 19(9):989–1003CrossRefGoogle Scholar
  35. 35.
    Ni L, Liu Y, Lau Y, Patil A (2004) LANDMARC: indoor location sensing using active RFID. Wirel Netw 10(6):701–710CrossRefGoogle Scholar
  36. 36.
    O’Cualain D, Jones E, Glavin M (2010) Distance determination for an automobile environment using inverse perspective mapping in OpenCV. In Proc. of Signals and Systems Conference, pp 100–105Google Scholar
  37. 37.
    Ozdenizci B, Ok K, Coskun V, Aydin M (2011) Development of an indoor navigation system using NFC technology. In Proc. of Fourth International Conference on Information and Computing, pp 11–14Google Scholar
  38. 38.
    Pauleve L, Jegou H, Amsaleg L (2010) Locality sensitive hashing: a comparison of hash function types and querying mechanisms. J Pattern Recognit Lett 31(11):1348–1358CrossRefGoogle Scholar
  39. 39.
    Renaudin V, Yalak O, Tome P, Merminod B (2007) Indoor navigation of emergency agents. Eur J Navig 5:36–45Google Scholar
  40. 40.
    Ruotsalainen L, Kuusniemi H, Chen R (2011) Visual-aided two-dimensional pedestrian indoor navigation with a smartphone. J Glob Positioning Syst 10 (1):11–18CrossRefGoogle Scholar
  41. 41.
    Satalich G (1995) Navigation and Wayfinding in virtual reality: Finding proper tools and cues to enhance navigation awareness. Master’s thesis, University of WashingtonGoogle Scholar
  42. 42.
    Schmid C, Mohr R, Bauckhage C (2000) Evaluation of interest point detectors. Int J Comput Vis 37(2):151–172CrossRefzbMATHGoogle Scholar
  43. 43.
    Slipa-Anan C, Hartley R (2004) Localisation using an image-map. ACRCGoogle Scholar
  44. 44.
    Thongthammacharl S, Olesen H (2003) Bluetooth enables indoor mobile location services. In Proc. of the 57th IEEE semiannual vehicular technology conference, vol. 3, pp 2023–2027Google Scholar
  45. 45.
    Wang Z, Bovik AC (2009) Mean squared error: love it or leave it? IEEE signal processing, pp 98–117Google Scholar
  46. 46.
    Wang Y, Jia X, Lee HK, Li GY (2003) An indoors wireless positioning system based on wireless local area network infrastructure. In the 6th International Symposium on Satellite Navigation technology including Mobile Positioning & Location Services, Melbourne, AustraliaGoogle Scholar
  47. 47.
    Want R, Hooper A, Falcao V, Gibbons J (1992) The active badge location system. ACM Trans Inf Syst 10(1):91–102CrossRefGoogle Scholar
  48. 48.
    Werner M, Kessel M, Marouane C (2011) Indoor positioning using smartphone camera. In Proc. of International Conference on Indoor Positioning and Indoor Navigation (IPIN), Portugal, pp 21–23Google Scholar
  49. 49.
    West DB (2001) Introduction to graph theory second edition. Singapore: Pearson Education, pp 97–98Google Scholar
  50. 50.
    Yazawa N, Uchiyama H, Saito H, Servieres M, Moreau G (2009) Image based view localization system retrieving from a panorama database by SURF. In Proc. of the IAPR Conference on Machine Vision ApplicationsGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Auckland University of TechnologyAucklandNew Zealand

Personalised recommendations