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Conference Papers Year : 2004

Motion Prediction for Moving Objects: a Statistical Approach

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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.
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Dates and versions

inria-00182066 , version 1 (24-10-2007)

Identifiers

  • HAL Id : inria-00182066 , version 1

Cite

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. ⟨inria-00182066⟩
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