Dealing with occlusions with multi targets tracking algorithms for the real road context
Laetitia Lamard, Roland Chapuis, Jean-Philippe Boyer · 2012
In this paper, we present a robust approach to occlusion problems for tracking vehicle and pedestrian on road context. Most multi-target tracking algorithms, like Multiple Hypothesis Tracker (MHT) or Cardinalized Probability Hypothesis Density (CPHD), are based on a sensor detection probability map. This paper proposes to solve the occlusion issue by modifying this detection probability map. We assume targets occlusion is provided by other targets and are treated as non detection event. The new detection probability map is computed by taking into account the width and the imprecision of the position of the targets that hide the others. Our system has been validated with simulated data and also with real measurements from a smart camera sensor embedded in a real car for road context.