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DOI : 10.1109/TKDE.2011.39

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IEEE Transactions on Knowledge and Data Engineering (2011) 1-17

Segmentation and sampling of moving object trajectories based on representativeness.

Costas Panagiotakis 1, Nikos Pelekis 2, Ioannis Kopanakis 3, Emmanuel Ramasso 4, Yannis Theodoridis 5

(02/2011)

Moving Object Databases (MOD), although ubiquitous, still call for methods that will be able to understand, search, analyze, and browse their spatiotemporal content. In this paper, we propose a method for trajectory segmentation and sampling based on the representativeness of the (sub-)trajectories in the MOD. In order to find the most representative sub-trajectories, the following methodology is proposed. First, a novel global voting algorithm is performed, based on local density and trajectory similarity information. This method is applied for each segment of the trajectory, forming a local trajectory descriptor that represents line segment representativeness. The sequence of this descriptor over a trajectory gives the voting signal of the trajectory, where high values correspond to the most representative parts. Then, a novel segmentation algorithm is applied on this signal that automatically estimates the number of partitions and the partition borders, identifying homogenous partitions concerning their representativeness. Finally, a sampling method over the resulting segments yields the most representative sub-trajectories in the MOD. Our experimental results in synthetic and real MOD verify the effectiveness of the proposed scheme, also in comparison with other sampling techniques.

1 :	Computer Science Department (CSD-UOC)
	Institute of Computer Science – University of Crete
2 :	Dept. of Statistics and Insurance Science.
	University of Piraeus
3 :	Dept. of Commerce and Marketing.
	University of Piraeus
4 :	Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (FEMTO-ST)
	CNRS : UMR6174 – Université de Franche-Comté – Université de Technologie de Belfort-Montbeliard – Ecole Nationale Supérieure de Mécanique et des Microtechniques
5 :	Dept. of Informatics.
	University of Piraeus

Équipe de recherche : AS2M/Cosmi

Domaine

:

Sciences de l'ingénieur/Automatique / Robotique

Mots Clés : Trajectory segmentation – subtrajectory sampling – data mining – moving object databases.

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Contributeur : Martine Azema <>

Soumis le : Mercredi 13 Avril 2011, 14:56:55

Dernière modification le : Mercredi 13 Avril 2011, 16:12:46