A New Measurement Method to Calculate Similarity of Moving Object Spatio-Temporal Trajectories by Compact Representation

Abstract

A new measurement method is proposed to calculate spatio-temporal trajectory similarity, which can reflect the similar degree between two moving object spatio-temporal trajectories compressed by the Maximal Bounding Boxes (MBB). Firstly, the similarity between two trajectories is replaced by the similarity of MBB sequences in respective trajectories which can dramatically decrease the storage volume of the trajectory data. Secondly, some factors affected the similar degree of MBB sequences are analyzed systematically, such as the time duration of overlap between two MBBs in different trajectories, space distance and the density of data points inside the boxes. And then, a similarity measurement formula is proposed by integrating these factors. Experiments show that the proposed measurement formula can improve the value of clustering index Dunn.

Keywords:

• Spatio-temporal data mining
• moving object trajectories
• trajectory similarity degree
• similarity measurement formula