In this paper, the problem of targets road tracking, like pedestrians and vehicles tracking is addressed. This paper proposes to improve a Cardinalized Probability Hypothesis Density (CPHD) filter in presence of occlusion using the sensor classification of each targets detected. Using this classification, a probability of target type is computed by Bayesian rules and used to deduce the width of targets. This width is necessary to take into account the occlusion problem in the Multi Target Tracking (MTT) filter. Besides, the probability of target type is also used to improve the performance of this MTT thanks to a new computation of the likelihood of measurements. Our system has been validated with real measurements from a smart camera in real traffic conditions.
CPHD filter addressing occlusions with pedestrians and vehicles tracking
2013 IEEE Intelligent Vehicles Symposium (IV) ; 1125-1130
2013-06-01
701954 byte
Conference paper
Electronic Resource
English
CPHD FILTER ADDRESSING OCCLUSIONS WITH PEDESTRIANS AND VEHICLES TRACKING
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