Direction-Preserving Trajectory Simplification

Trajectories of moving objects are collected in many applications. Raw trajectory data is typically very large, and has to be simplified before use. In this paper, we introduce the notion of directionpreserving trajectory simplification, and show both analytically and empirically that it can support a broader range of applications than traditional position-preserving trajectory simplification. We present a polynomial-time algorithm for optimal directionpreserving simplification, and another approximate algorithm with a quality guarantee. Extensive experimental evaluation with real trajectory data shows the benefit of the new techniques.