ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis c...

Full description

Saved in:
Bibliographic Details
Published in:The Visual computer 2016-06, Vol.32 (6-8), p.847-857
Main Authors: Cibulski, Lena, Gračanin, Denis, Diehl, Alexandra, Splechtna, Rainer, Elshehaly, Mai, Delrieux, Claudio, Matković, Krešimir
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Graphics
Computer Science
Data analysis
Datasets
Image Processing and Computer Vision
Original Article
Trajectory analysis
Visualization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include on-the-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.
ISSN:0178-2789
1432-2315
DOI:10.1007/s00371-016-1255-7