Human tracking with variable prediction steps based on Kullback-Leibler divergence

This article deals with a path-planning problem in tracking humans in order to obtain detailed information about human behavior and characteristics. In our method, path planning is performed based on Kullback-Leibler (KL) divergence between the predicted distribution of all human positions and the intensity of the field of view of the agents. The number of steps predicted is determined according to the consistency of the prediction. Experimental results show that when the prediction of human movement is accurate, long-term prediction is useful for path planning. On the other hand, when prediction is inaccurate, long-term prediction might not be useful. Our path-planning method works well even under changing circumstances by changing the length of the predictions.