Tour the world: a technical demonstration of a web-scale landmark recognition engine

ABSTRACT

We present a technical demonstration of a world-scale touristic landmark recognition engine. To build such an engine, we leverage ~21.4 million images, from photo sharing websites and Google Image Search, and around two thousand web articles to mine the landmark names and learn the visual models. The landmark recognition engine incorporates 5312 landmarks from 1259 cities in 144 countries. This demonstration gives three exhibits: (1) a live landmark recognition engine that can visually recognize landmarks in a given image; (2) an interactive navigation tool showing landmarks on Google Earth; and (3) sample visual clusters (landmark model images) and a list of 1000 randomly selected landmarks from our recognition engine with their iconic images.

REFERENCES

• 1: J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. Commun. ACM, 51(1):107--113, 2008.
• 2: D. G. Lowe. Object recognition from local scale-invariant features. In ICCV 99, pages 1150--1157, 1999.
• 3: Y.-T. Zheng, M. Zhao, Y. Song, H. Adam, U. Buddemeier, A. Bissacco, F. Brucher, T.-S. Chua, and H. Neven. Tour the world: building a web-scale landmark recognition engine. In Proceedings of International Conference on Computer Vision and Pattern Recognition, Miami, Florida, U.S.A, June, 2009.

INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.7 COMPUTERS IN OTHER SYSTEMS
      Subjects: Consumer products

General Terms:
Algorithms

Keywords:
touristic landmark recongition