Trajectory Simplification Algorithm based on Structure Features - Zhu, Mingjun (IJRDO -Journal of Computer Science Engineering, 2019)
With the extensive use of location based devices, trajectories of various kind of moving objects can be collected. As time going on, the amount of trajectory data increases exponentially, which brings a series of problems in storage, transmission and analysis. Current trajectory compression algorithms mainly focus on position preserving, compress ratio and run efficiency, but neglect the movement features in trajectories. In this paper, we propose a novel three-stage trajectory compression algorithm based on moving direction of objects, internal fluctuation in trajectories and trajectory velocity, which takes full account of movement pattern and structure features in trajectories. Firstly, the raw trajectory is compressed based on moving direction and the velocity of the object. Then, the trajectory is further simplified according to internal fluctuation in raw trajectory. Comprehensive experiments on real dataset show that: not only the efficiency and effectiveness of the proposed work is better, but also the reservation of local movement features of moving objects and internal characteristic information in trajectories is more detailed.