Trajectory prediction (TP) of moving objects has grown rapidly to be a new exciting paradigm. However, existing prediction algorithms mainly employ kinematical models to approximat...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
We explore the capability of the Self Organizing Map for structured data (SOM-SD) to compress continuous time data recorded from a kinematic tree, which can represent a robot or an...
Trajectory classification, i.e., model construction for predicting the class labels of moving objects based on their trajectories and other features, has many important, real-worl...
A common problem in moving object databases (MOD) is the reconstruction of a trajectory from a trajectory sample (i.e., a finite sequence of time-space points). A typical solution...
Alejandro A. Vaisman, Bart Kuijpers, Bart Moelans,...