Motion Prediction for Moving Objects: a Statistical Approach

Dizan Alejandro Vasquez Govea 1 Thierry Fraichard 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes
Abstract : This paper proposes a technique to obtain long term estimates of the motion of a moving object in a structured environment. Objects moving in such environments often participate in typical motion patterns which can be observed consistently. Our technique learns those patterns by observing the environment and clustering the observed trajectories using any pairwise clustering algorithm. We have implemented our technique using both simulated and real data coming from a vision system. The results show that the technique is general, produces long-term predictions and is fast enough for its use in real time applications.
Type de document :
Communication dans un congrès
Proc. of the IEEE Int. Conf. on Robotics and Automation, Apr 2004, New Orleans, LA (US), France. pp.3931--3936, 2004
Liste complète des métadonnées

Littérature citée [19 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00182066
Contributeur : Christian Laugier <>
Soumis le : mercredi 24 octobre 2007 - 18:45:37
Dernière modification le : mercredi 11 avril 2018 - 01:54:13
Document(s) archivé(s) le : lundi 12 avril 2010 - 00:34:57

Fichiers

Identifiants

  • HAL Id : inria-00182066, version 1

Collections

INRIA | UGA | IMAG

Citation

Dizan Alejandro Vasquez Govea, Thierry Fraichard. Motion Prediction for Moving Objects: a Statistical Approach. Proc. of the IEEE Int. Conf. on Robotics and Automation, Apr 2004, New Orleans, LA (US), France. pp.3931--3936, 2004. 〈inria-00182066〉

Partager

Métriques

Consultations de la notice

220

Téléchargements de fichiers

2884