Generalized distance metric as a robust similarity measure for mobile object trajectories

In this paper, we propose a novel generalized distance metric based on a model that incorporates the time axis explicitly. The proposed metric is based fundamentally on the Mahalanobis distance metric, which eliminates the correlation and scaling errors in similarity searches on trajectory databases. We propose the incorporation of a weight matrix in the proposed distance metric, which allows for easy manipulation of the degree of significance of the different spatial and or temporal dimensions.