Discovering loose group movement patterns from animal trajectories
Links
- More information: Publisher Index Page (via DOI)
- Download citation as: RIS | Dublin Core
Abstract
The technical advances of positioning technologies enable us to track animal movements at finer spatial and temporal scales, and further help to discover a variety of complex interactive relationships. In this paper, considering the loose gathering characteristics of the real-life groups' members during the movements, we propose two kinds of loose group movement patterns and corresponding discovery algorithms. Firstly, we propose the weakly consistent group movement pattern which allows the gathering of a part of the members and individual temporary leave from the whole during the movements. To tolerate the high dispersion of the group at some moments (i.e. to adapt the discontinuity of the group's gatherings), we further scheme the weakly consistent and continuous group movement pattern. The extensive experimental analysis and comparison with the real and synthetic data shows that the group pattern discovery algorithms proposed in this paper are similar to the the real-life frequent divergences of the members during the movements, can discover more complete memberships, and have considerable performance.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Discovering loose group movement patterns from animal trajectories |
| DOI | 10.1109/eScience.2015.30 |
| Year Published | 2015 |
| Language | English |
| Publisher | IEEE |
| Contributing office(s) | Patuxent Wildlife Research Center |
| Description | 11 p. |
| Larger Work Type | Conference Paper |
| Larger Work Subtype | Conference Paper |
| Larger Work Title | 2015 IEEE 11th International Conference on e-Science |
| First page | 196 |
| Last page | 206 |
| Conference Title | 2015 IEEE 11th International Conference on e-Science |
| Conference Location | Munich, Germany |
| Conference Date | August 31, 2015 |
| Online Only (Y/N) | N |
| Additional Online Files (Y/N) | N |
| Google Analytic Metrics | Metrics page |