A New Framework for Criteria-­based Trajectory Segmentation

1. A New Framework for Criteria-­based Trajectory Segmentation Kevin Buchin Joint work with Sander Alewijnse, Maike Buchin, Andrea Kölzsch, Helmut Kruckenberg and Michel Westenberg September 30, 2013

2. Stopovers in Geese Migration

3. Goal • Delineate stopover sites of migratory geese • Two behavioural types • stopover • migration flight • Input: • GPS tracks • expert description of behaviour

4. Data • Spring migration tracks • White-fronted geese • 4-5 positions per day • March – June • Up to 10 stopovers during spring migration • Stopover: 48 h within radius 30 km • Flight: change in heading <120°

5. Criteria • Decreasing criteria • Increasing criteria stopover migration flight Within radius 30km Within radius 30km At least 48h At least 48h • Change in heading • <120° • Change in heading • <120° AND OR

6. Criteria-based Segmentation New Framework [M. Buchin et al. 2011] [M. Buchin et al. 2012] [Aronov et al. 2013] • decreasing criteria • increasing criteria • approx. outliers • Brownian bridges • near-linear time • decreasing criteria • min-duration • few outliers • general quadratic time • results on continuous segmentation • decreasing criteria

7. Demo 1

8. Criteria-based Segmentation New Framework [M. Buchin et al. 2011] [M. Buchin et al. 2012] [Aronov et al. 2013] [Kranstauber et al. 2012] • decreasing criteria • increasing criteria • approx. outliers • Brownian bridges • near-linear time • decreasing criteria • min-duration • few outliers • general quadratic time • results on continuous segmentation • decreasing criteria • dynamic Brownian bridges • not about segmentation

9. Segment by diffusion coefficient

10. Demo 2

11. Summary • Criteria-based Segmentation to identify behavioural states • Efficient algorithms for a large class of criteria • Also handles criteria AND Brownian bridges • Case studies: both criteria-based and Brownian bridges work well Thanks!