Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive Maps for a Digital Video Library
IEEE MultiMedia
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Multimodal Video Indexing: A Review of the State-of-the-art
Multimedia Tools and Applications
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Tracking news stories across different sources
Proceedings of the 13th annual ACM international conference on Multimedia
Proceedings of the 13th annual ACM international conference on Multimedia
Effective Density Queries on ContinuouslyMoving Objects
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
Video suggestion and discovery for youtube: taking random walks through the view graph
Proceedings of the 17th international conference on World Wide Web
Web video topic discovery and tracking via bipartite graph reinforcement model
Proceedings of the 17th international conference on World Wide Web
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
Viewable scene modeling for geospatial video search
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Parallel neural networks for multimodal video genre classification
Multimedia Tools and Applications
A Hybrid Prediction Model for Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
MOIR/MT: monitoring large-scale road network traffic in real-time
Proceedings of the VLDB Endowment
Annotating and navigating tourist videos
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
W2Go: a travel guidance system by automatic landmark ranking
Proceedings of the international conference on Multimedia
Photo2Trip: generating travel routes from geo-tagged photos for trip planning
Proceedings of the international conference on Multimedia
Topic discovery of web video using star-structured K-partite graph
Proceedings of the international conference on Multimedia
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
Mining flickr landmarks by modeling reconstruction sparsity
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special section on ACM multimedia 2010 best paper candidates, and issue on social media
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Hot event detection and summarization by graph modeling and matching
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
TrajPattern: mining sequential patterns from imprecise trajectories of mobile objects
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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As video data generated by users boom continuously, making sense of large scale data archives is considered as a critical challenge for data management. Most existing learning techniques that extract signal-level contents from video data struggle to scale due to efficiency limits. With the development of pervasive positioning techniques, discovering hot topics from multimedia data by their geographical tags has become practical: videos taken by advanced cameras are associated with GPS locations, and geo-tagged videos from YouTube can be identified by their associated GPS locations on Google Maps. It enables us to know the cultures, scenes, and human behaviors from videos based on their spatio-temporal distributions. However, meaningful topic discovery requires an efficient clustering approach, through which coherent topics can be detected according to particular geographical regions without out-of-focus effects. To handle this problem, this paper presents a filter-refinement framework to discover hot topics corresponding to geographical dense regions, and then introduces two novel metrics to refine unbounded hot regions, together with a heuristic method for setting rational thresholds on these metrics. The results of extensive experiments prove that hot topics can be efficiently discovered by our framework, and more compact topics can be achieved after using the novel metrics.