In this paper we address the problem of segmenting a trajectory based on spatiotemporal criteria. We require that each segment is homogeneous in the sense that a set of spatiotemporal criteria are fulfilled. We define different such criteria, including location, heading, speed, velocity, curvature, sinuosity, curviness, and shape. We present an algorithmic framework that allows us to segment any trajectory into a minimum number of segments under any of these criteria, or any combination of these criteria. In this framework, a segmentation can generally be computed in O(n log n) time, where n is the number of edges of the trajectory to be segmented. We also discuss the robustness of our approach.
The segmentation problem is defined as follows: to split a high-sampling rate trajectory into a minimum number of segments such that the movement characteristic inside each segment is uniform in some sense REF .
Segmenting trajectories: A framework and algorithms using spatiotemporal criteria
J. Spatial Information Science
J. Spatial Information Science
Computer Science