In this paper, an algorithm for tracking multiple non-rigid objects in cluttered scenes is presented. The proposed approach models the shape of the objects by using corners. In particular, a learning algorithm is introduced in order to automatically extract an adaptive model of the object. The obtained adaptive model is used to individuate the object position and scale when occlusions are present. The method is used on an existing video-surveillance system in order to track moving object in cluttered scenes. Results show that the proposed approach provides good performances with low processing times.

Robust tracking of humans and vehicles in cluttered scenes with occlusions

REGAZZONI, CARLO
2002-01-01

Abstract

In this paper, an algorithm for tracking multiple non-rigid objects in cluttered scenes is presented. The proposed approach models the shape of the objects by using corners. In particular, a learning algorithm is introduced in order to automatically extract an adaptive model of the object. The obtained adaptive model is used to individuate the object position and scale when occlusions are present. The method is used on an existing video-surveillance system in order to track moving object in cluttered scenes. Results show that the proposed approach provides good performances with low processing times.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/840889
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