Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
ClustTour: city exploration by use of hybrid photo clustering
Proceedings of the international conference on Multimedia
Research and applications on georeferenced multimedia: a survey
Multimedia Tools and Applications
City exploration by use of spatio-temporal analysis and clustering of user contributed photos
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Near2me: an authentic and personalized social media-based recommender for travel destinations
WSM '11 Proceedings of the 3rd ACM SIGMM international workshop on Social media
Mining Travel Patterns from Geotagged Photos
ACM Transactions on Intelligent Systems and Technology (TIST)
Cluster-based photo browsing and tagging on the go
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks
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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.