A DSmT-Based approach for data association in the context of multiple target tracking

Authors:
Mohamed Airouche;Layachi Bentabet;Mimoun Zelmat
Affiliations:
Applied Automation Laboratory, FHC, Boumerdes University, Boumerdes, Algeria, Computer Sciences Department, Bishop's University, Sherbrooke, Canada;Computer Sciences Department, Bishop's University, Sherbrooke, Canada;Applied Automation Laboratory, FHC, Boumerdes University, Boumerdes, Algeria
Venue:
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Year:
2012

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Abstract

This paper presents a multiple target tracking method that uses the Dezert-Smarandache Theory (DSmT) for data association. A detailed framework is developed to show how the DSmT can be used to associate measurements with the corresponding correct targets. We will discuss the choices of the tracking hypotheses in the DSmT and we will demonstrate the effectiveness of the developed approach on simulated and real tracking scenarios that uses color and infrared cues.