Spatio-Temporal Trajectory Region-of-Interest Mining Using Delaunay Triangulation

Author

Bermingham, Luke ; Kyungmi Lee ; Lee, Inkyu

Author_Institution

Coll. of Bus., James Cook Univ., Cairns, QLD, Australia

fYear

2014

fDate

14-14 Dec. 2014

Firstpage

1

Lastpage

8

Abstract

Due to the ubiquity of GPS enabled devices and the advances in sensing technologies, trajectory data has become abundant. Regions of interest are important since they describe specific hot-spots within the data that often correlate with domain specific phenomena. Traditional region of interest mining utilises grid based rasters to model space. This suffers from two main problems: hard to determine the best grid size and unable to model consistent spatial adjacency. This paper utilises a 3D argument free space tessellation, Delaunay triangulation, to partition spatio-temporal trajectory data and extract arbitrary shaped regions of interest. Experimental results demonstrate the robustness and improved effectiveness of our approach at identifying granular spatio-temporal patterns.

Keywords

computer graphics; data mining; mesh generation; 3D argument free space tessellation; Delaunay triangulation; GPS enabled devices; consistent spatial adjacency; domain specific phenomena; granular spatio-temporal patterns; grid based rasters; model space; spatio-temporal trajectory data; spatio-temporal trajectory region-of-interest mining; Australia; Cities and towns; Data mining; Equations; Face; Three-dimensional displays; Trajectory; Trajectory; delaunay; region of interest;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Mining Workshop (ICDMW), 2014 IEEE International Conference on

Conference_Location

Shenzhen

Print_ISBN

978-1-4799-4275-6

Type

conf

DOI

10.1109/ICDMW.2014.47

Filename

7022570