Smart Tourist Guide with Image Understanding Using Visual Instance Search

  • Minh-Duc NguyenEmail author
  • Thanh-An Than
  • Vinh-Tiep Nguyen
  • Minh-Triet Tran
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9733)


To get useful information on a landmark and to activate appropriate interaction related to that landmark can be a useful utility on mobile devices for travelers, especially in new visiting places. This motivates our proposal to use visual instance search to develop an interactive smart tourist guide system. Our aim is to provide not only a more accurate way to recommend a landmark and its information but also interesting and useful interactions around the landmark in order to seamlessly integrate real life interaction with the retrieved information. First, we develop our visual instance search framework that is optimized for speed and can achieve the accuracy approximating novel methods. Then, we apply our framework to the landmark recognition problem to replace the traditional approach of classification. Lastly, we apply our framework to our smart tourist guide system to identify a landmark, to provide its information as well as related interactions when given a landmark image. By incorporating visual instance search and interactive information, we can provide more accurate and seamlessly natural way of searching and interacting with landmarks for passengers and visitors in tourism.


Visual instance search Smart tourist guide Landmark recognition 


  1. 1.
    Torii, A., Sivic, J., Pajdla, T., Okutomi, M.: Visual place recognition with repetitive structures. In: CVPR, Portland, OR (2013)Google Scholar
  2. 2.
    Arandjelovic, R., Zisserman, A.: Three things everyone should know to improve object retrieval. In: CVPR, Providence, RI (2012)Google Scholar
  3. 3.
    Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: CVPR, Minneapolis, MN (2007)Google Scholar
  4. 4.
    Chum, O., Philbin, J., Sivic, J., Isard, M., Zisserman, A.: Total recall: automatic query expansion with a generative feature model for object retrieval. In: ICCV, Rio de Janeiro (2007)Google Scholar
  5. 5.
    Shao, H., Svoboda, T., Van Gool, L.: Zubud-zurich buildings database for image based recognition. Technical report 260 (2003)Google Scholar
  6. 6.
    Aly, M., Welinder, P., Munich, M., Perona, P.: Towards automated large scale discovery of image families. In: Second IEEE Workshop on Internet Vision, CVPR, Miami, Florida (2009)Google Scholar
  7. 7.
    Sivic, J., Zisserman, A.: Video Google: a text retrieval approach to object matching in videos. In: Computer Vision, Nice, France (2003)Google Scholar
  8. 8.
    Perd’och, M., Chum, O., Matas, J.: Efficient representation of local geometry for large scale object retrieval. In: CVPR, Miami, FL (2009)Google Scholar
  9. 9.
    Muja, M., Lowe, D.G.: Fast approximate nearest neighbours with automatic algorithm configuration. In: VISAPP (2009)Google Scholar
  10. 10.
    Marée, R., Geurts, P., Piater, J., Wehenkel, L.: Decision trees and random subwindows for object recognition. In: ICML Workshop on Machine Learning Techniques for Processing Multimedia Content (2005)Google Scholar
  11. 11.
    Groeneweg, N.J., de Groot, B., Halma, A.H., Quiroga, B.R., Tromp, M., Groen, F.C.: A fast offline building recognition application. In: Advanced Concepts for Intelligent Vision Systems (2006)Google Scholar
  12. 12.
    Matas, J., Obdrzalek, S.: Object recognition methods based on transformation. In: EUSIPCO (2004)Google Scholar
  13. 13.
    Casanova, C., Franco, A., Lumini, A., Maio, D.: SmartVisionApp: a framework for computer vision applications on mobile devices. In: Expert Systems with Applications, pp. 5884–5894 (2013)Google Scholar
  14. 14.
    Hedau, V., Sinha, S.N., Zitnick, C., Szeliski, R.: A memory efficient discriminative approach for location aided recognition. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 187–197. Springer, Heidelberg (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Minh-Duc Nguyen
    • 1
    • 2
    Email author
  • Thanh-An Than
    • 1
    • 2
  • Vinh-Tiep Nguyen
    • 3
  • Minh-Triet Tran
    • 3
  1. 1.Advance Program in Computer ScienceUniversity of Science, VNU-HCMHo Chi Minh CityVietnam
  2. 2.John von Neumann Institute, VNU-HCMHo Chi Minh CityVietnam
  3. 3.Faculty of Information TechnologyUniversity of Science, VNU-HCMHo Chi Minh CityVietnam

Personalised recommendations