Predictive Estimation Method to Track Occluded Multiple Objects Using Joint Probabilistic Data Association Filter

Abstract

In multi-target visual tracking, tracking failure due to miss-association can often arise from the presence of occlusions between targets. To cope with this problem, we propose the predictive estimation method that iterates occlusion prediction and occlusion status update using occlusion activity detection by utilizing joint probabilistic data association filter in order to track each target before, during and after occlusion. First, the tracking system predicts the position of a target, and occlusion activity detection is performed at the predicted position to examine if an occlusion activity is enabled. Second, the tracking system re-computes positions of occluded targets and updates them if an occlusion activity is enabled. Robustness of multi-target tracking using predictive estimation method is demonstrated with representative simulations.