Scalable analysis of movement data for extracting and exploring significant places
Andrienko G., Andrienko N., Hurter C., Rinzivillo S., Wroebel S.
time series analysis visualization Event detection data mining trajectories spatial clustering Computer Vision and Pattern Recognition [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC] spatiotemporal clustering Computer Graphics and Computer-Aided Design Mobility data mining Clustering spatiotemporal data trajectory Interactive data exploration and discovery Signal Processing cities and towns spatial events Data visualization context image color analysis Software GA movement
Place-oriented analysis of movement data, i.e., recorded tracks of moving objects, includes finding places of interest in which certain types of movement events occur repeatedly and investigating the temporal distribution of event occurrences in these places and, possibly, other characteristics of the places and links between them. For this class of problems, we propose a visual analytics procedure consisting of four major steps: (1) event extraction from trajectories; (2) extraction of relevant places based on event clustering; (3) spatio-temporal aggregation of events or trajectories; (4) analysis of the aggregated data. All steps can be fulfilled in a scalable way with respect to the amount of the data under analysis; therefore, the procedure is not limited by the size of the computer's RAM and can be applied to very large datasets. We demonstrate the use of the procedure by example of two real-world problems requiring analysis at different spatial scales.
Source: IEEE transactions on visualization and computer graphics (Online) 19 (2013): 1078–1094. doi:10.1109/TVCG.2012.311
Publisher: IEEE Computer Society,, New York, NY , Stati Uniti d'America
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@article{oai:it.cnr:prodotti:216401,
title = {Scalable analysis of movement data for extracting and exploring significant places},
author = {Andrienko G. and Andrienko N. and Hurter C. and Rinzivillo S. and Wroebel S.},
publisher = {IEEE Computer Society,, New York, NY , Stati Uniti d'America},
doi = {10.1109/tvcg.2012.311},
journal = {IEEE transactions on visualization and computer graphics (Online)},
volume = {19},
pages = {1078–1094},
year = {2013}
}
0000-0003-4404-4147
