In this paper we describe the application of Particle Swarm Optimisation to the problem of human body pose estimation from multiple view video sequences. We use a subdivision body model with an underlying skeleton layer to estimate and illustrate the body pose. The optimisation looks for the best match between the silhouettes extracted from the original video sequence and the silhouettes generated by the projection of the model in a pose suggested by the PSO. The original PSO algorithm is applied hierarchically and combined with the full overall optimisation to decrease the effects of error propagation. Results demonstrate the ability of PSO to reliably recover the correct body pose from 4-viewpoint video sequences.