Multiple target tracking in video data using labeled random finite set

Abstract

This paper demonstrates how the d-Generalized Labeled Multi-Bernoulli (d-GLMB) filter can be applied to track moving targets on videos. The tracking is performed directly on the original images which are not preprocessed into point measurements and estimates the number of targets on frame along with their states. In that sense this concept bears resemblance to the track before detect (TBD) approach employed under low signal to noise ratio conditions. Image sequences from the CAVIAR1 dataset are used in simulations to prove the aptitude of this method.