Vector field k-means: Clustering trajectories by fitting multiple vector fields

Computer Graphics Forum

Volumn 32, Issue 3 PART2, 2013, Pages 201-210

  Ferreira, Nivan ^a   Klosowski, James T ^b   Scheidegger, Carlos E ^b   Silva, Cláudio T ^a  

^a POLYTECHNIC UNIVERSITY   (United States)

^b AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HURRICANES; TRAJECTORIES;

EFFECTIVENESS AND EFFICIENCIES; EXPERIMENTAL EVIDENCE; MOVEMENT PATTERN; MULTIPLE VECTORS; OPTIMAL CLUSTERING; SERVICE PROVIDER; TRAFFIC ANALYSIS; TRAJECTORY CLUSTERING;

VECTORS;

EID: 84879740999     PISSN: 01677055     EISSN: 14678659     Source Type: Journal    
DOI: 10.1111/cgf.12107     Document Type: Article

References (36)

1. Andrienko G., Andrienko N.,: Spatio-temporal aggregation for visual analysis of movements. In IEEE Symposium on Visual Analytics Science and Technology (2008), pp. 51-58. 3.
2. Andrienko N., Andrienko G.,: Spatial generalization and aggregation of massive movement data. IEEE Trans. Visualization and Computer Graphics 17, 2 (2011), 205-219. 3.
3. Andrienko G., Andrienko N., Hurter C., Rinzivillo S., Wrobel S.,: From movement tracks through events to places: Extracting and characterizing significant places from mobility data. In IEEE Symposium on Visual Analytics Science and Technology (2011), pp. 159-168. 3.
4. Andrienko G., Andrienko N., Rinzivillo S., Nanni M., Pedreschi D., Giannotti F.,: Interactive visual clustering of large collections of trajectories. In IEEE Symposium on Visual Analytics Science and Technology (2009), pp. 3-10. 3.
5. Andrienko G., Andrienko N., Wrobel S.,: Visual analytics tools for analysis of movement data. SIGKDD Explorations 9, 2 (2007), 38-46. 3.
6. Arthur D., Vassilvitskii S.,: k-means++: The advantages of careful seeding. In Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms (2007), Society for Industrial and Applied Mathematics, pp. 1027-1035. 9.
7. Becker R. A., Caceres R., Hanson K., Loh J. M., Urbanek S., Varshavsky A., Volinsky C.,: Route classification using cellular handoff patterns. In 13th International Conference on Ubiquitous Computing (2011), pp. 123-132. 1, 7.
8. Bayir M., Demirbas M., Eagle N.,: Discovering spatiotemporal mobility profiles of cellphone users. In IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks & Workshops (2009), pp. 1-9. 1.
9. Brillinger D., Preisler H., Ager A., Kie J.,: An exploratory data analysis (EDA) of the paths of moving animals. Statistical Planning and Inference 122, 2 (2004), 43-63. 1, 3.
10. Chen G., Kwatra V., Wei L., Hansen C., Zhang E.,: Design of 2d time-varying vector fields. IEEE Trans. Visualization and Computer Graphics 18, 10 (2012), 1717-1730. 9.
11. Camargo S. J., Robertson A. W., Gaffney S. J., Smyth P., Ghil M.,: Cluster analysis of typhoon tracks. Climate 20, 14 (2007), 3635-3676. 1, 3.
12. Daae Lampe O., Hauser H.,: Interactive visualization of streaming data with kernel density estimation. In IEEE Pacific Visualization Symposium (2011), pp. 171-178. 3.
13. Elsner J.,: Tracking hurricanes. Bulletin of the American Meteorological Society 84, 3 (2003), 353-356. 1.
14. Ferreira N., Lins L., Fink D., Kelling S., Wood C., Freire J., Silva C.,: BirdVis: Visualizing and understanding bird populations. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2374-2383. 1.
15. Fang Y., Wang J.,: Selection of the number of clusters via the bootstrap method. Comput. Stat. Data Anal. 56, 3 (Mar 2012), 468-477. 8.
16. Grundy E., Jones M. W., Laramee R. S., Wilson R. P., Shepard E. L.,: Visualisation of sensor data from animal movement. In Computer Graphics Forum (2009), vol. 28, Wiley Online Library, pp. 815-822. 1.
17. Gudmundsson J., Laube P., Wolle T.,: Computational movement analysis. Springer Handbook of Geographic Information (2012), 725-741. 1, 2, 3, 8.
18. HURDAT: The national hurricane center's north atlantic hurricane database, Feb 2012. URL: http://www.aoml.noaa.gov/hrd/data-sub/re-anal.html. 6.
19. Haklay M., Weber P.,: Openstreetmap: User-generated street maps. Pervasive Computing, IEEE 7, 4 (2008), 12-18. 9.
20. Jänicke H., Weidner T., Chung D., Laramee R. S., Townsend P., Chen M.,: Visual reconstructability as a quality metric for flow visualization. In Computer Graphics Forum (2011), vol. 30, Wiley Online Library, pp. 781-790. 3.
21. Kisilevich S., Mansmann F., Nanni M., Rinzivillo S.,: Spatio-temporal clustering. Data Mining and Knowledge Discovery Handbook (2010), 855-874. 2.
22. Lee J., Han J., Whang K.,: Trajectory clustering: a partition-and-group framework. In ACM SIGMOD International Conference on Management of Data (2007), pp. 593-604. 1, 2, 7.
23. Nascimento J. C., Figueiredo M. A. T., Marques J. S.,: Trajectory analysis in natural images using mixtures of vector fields. In IEEE International Conference on Image Processing (2009), pp. 4353-4356. 3.
24. Nocedal J., Wright S.,: Numerical optimization. Springer Verlag, 1999. 5.
25. Pelekis N., Kopanakis I., Kotsifakos E., Frentzos E., Theodoridis Y.,: Clustering trajectories of moving objects in an uncertain world. In Ninth IEEE International Conference on Data Mining (2009), pp. 417-427. 3.
26. Pu J., Xu P., Qu H., Cui W., Liu S., Ni L.,: Visual analysis of people's mobility pattern from mobile phone data. In Proceedings of Visual Information Communication-International Symposium (2011), pp. 13:1-13:10. 1.
27. Phan D., Xiao L., Yeh R., Hanrahan P., Winograd T.,: Flow map layout. In IEEE Symposium on Information Visualization (2005), pp. 219-224. 3.
28. Rinzivillo S., Pedreschi D., Nanni M., Giannotti F., Andrienko N., Andrienko G.,: Visually driven analysis of movement data by progressive clustering. Information Visualization 7, 3-4 (2008), 225. 1, 2, 3.
29. Sorkine O., Cohen-Or D., Irony D., Toledo S.,: Geometry-aware bases for shape approximation. IEEE Trans. Visualization and Computer Graphics 11, 2 (2005), 171-180. 4.
30. Scheepens R., Willems N., Van De Wetering H., Andrienko G., Andrienko N., Van Wijk J. J.,: Composite density maps for multivariate trajectories. IEEE Trans. Visual. and Computer Graphics 17, 12 (2011), 2518-2527. 3.
31. Tominski C., Schumann H., Andrienko G., Andrienko N.,: Stacking-based visualization of trajectory attribute data. IEEE Trans. Visualization and Computer Graphics 18, 12 (2012), 2565-2574. 1, 3.
32. Verbeek K., Buchin K., Speckmann B.,: Flow map layout via spiral trees. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2536-2544. 3.
33. Vallet B., Lévy B.,: Spectral geometry processing with manifold harmonics. Computer Graphics Forum (Proceedings Eurographics) (2008). 5, 8.
34. Willems N., Van De Wetering H., Van Wijk J. J.,: Visualization of vessel movements. Computer Graphics Forum (Proceedings of EuroVis) 28, 3 (2009), 959-966. 3.
35. Wei J., Yu H., Chen J., Ma K.,: Parallel clustering for visualizing large scientific line data. In IEEE Symposium on Large Data Analysis and Visualization (2011), pp. 47-55. 1.
36. Zheng Y., Xie X., Ma W.,: Geolife: A collaborative social networking service among user, location and trajectory. IEEE Data Engineering Bulletin 33, 2 (2010), 32-40. 6.