Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Proceedings of the 18th international conference on World wide web
Deducing trip related information from flickr
Proceedings of the 18th international conference on World wide web
Spectral clustering based on the graph p-Laplacian
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
GeoLife2.0: A Location-Based Social Networking Service
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Antourage: mining distance-constrained trips from flickr
Proceedings of the 19th international conference on World wide web
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
Using flickr geotags to predict user travel behaviour
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A recommendation system for spots in location-based online social networks
Proceedings of the 4th Workshop on Social Network Systems
A quad-tree based multiresolution approach for two-dimensional summary data
Information Systems
Exploiting geographical influence for collaborative point-of-interest recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Identifying points of interest by self-tuning clustering
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Localization of points of interest from georeferenced and oriented photographs
Proceedings of the 2nd ACM international workshop on Geotagging and its applications in multimedia
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Knowledge discovery in large online photographic repositories has been an active area of research in recent years. This is due to the great popularization of devices equipped with image capture, such as digital cameras, smartphones and tablets. Moreover, the image files generated by those devices are easily spread out on the Web through social networking sites. Typically, the photos stored in these repositories bear valuable metadata, such as, geographic coordinates, timestamp, and camera orientation. This information can be used for many interesting data mining tasks, such as detection of points-of-interest (POIs) and trip planning. This paper introduces Compass Clustering, a new clustering algorithm for detecting POIs in georeferenced and oriented photo repositories. Most of the state-of-the-art approaches for POI detection cluster photos based solely on their geographic proximity. However, in many cases, the POIs are within a certain distance from the point where the photo was taken, that is, not in the exact camera location but in the direction it is pointing to, and thus many photos would be erroneously classified by existing methods. Therefore, we propose to exploit the camera orientation in order to identify more reliable POIs that reflect the real intention of people when taking photos. We evaluated our approach on a collection of more than 8,000 georeferenced and oriented photos collected from Flickr.