Trajectories Modeling and Clustering
Boutaina Hdioud, Mohammed El Haj Tirari, Rachid Oulad Haj Thami · 2018
1 The location of moving objects facilitates the monitoring of their evolution and the history of displacement offers interesting perspectives in the field of the study of the behavior of these objects. The purpose of this paper is to provide a new methodology for constructing object trajectories based on a matching process that implements different features such as occultation management, surface, histogram, and so on. a second objective was to propose a classification approach of its trajectories. The proposed algorithm consists in classifying its trajectories in homogenous groups and isolating aberrant trajectories that exhibit deviant behavior. Its principle is based on the transformation of trajectories into spaces of distinct characteristics. These spaces make it possible to provide additional information on the characteristics of the model of movement of an object in a video sequence. The approach then consists in using the Mean-Shift algorithm to estimate the groups in each characteristic space. Clusters with the small number of associated trajectories and trajectories that are far from the center of the groups are considered outliers.