A comparative study of similarity evaluation methods among trajectories of moving objects

Abstract

© 2018 Evaluating similarity between moving objects’ trajectories has gained much attention in many application domains. There exist similarity measures in the literature that propose evaluating similarity between trajectories in the form of time stamped values. Their main drawback is that the similarity evaluation is affected by the different sampling rates as it is defined over sequences of time stamped values. One of these measures is the Time Warp Edit distance measure that was our base of measuring similarity in our TWEDistance operator. Therefore, in this paper, a comparative study is made between four different approaches: TWEDistance operator, regression, interpolation and curve barcoding. Similarity evaluation is made over trajectories of different sampling rates. Results show that interpolation achieves the highest accuracy compared to the other approaches with an average accuracy up to 90%. Experimental evaluation was made over synthetic and real datasets.