Tracking pedestrians with bacterial foraging optimization swarms
Hoang Thanh Nguyen, Bir Bhanu · 2011
Pedestrian tracking is an important problem with many practical applications in fields such as security, animation, and human computer interaction (HCI). In this paper, we introduce a previously-unexplored swarm intelligence approach to multi-object monocular tracking by using Bacterial Foraging Optimization (BFO) swarms to drive a novel part-based pedestrian appearance tracker. We show that tracking a pedestrian by segmenting the body into parts outperforms popular blob based methods and that using BFO can improve performance over traditional Particle Swarm Optimization and Particle Filter methods.