Efficient acquisition of human existence priors from motion trajectories

Abstract

This paper proposes a method for acquiring the prior probability of human existence by using past human trajectories and the color of an image. The priors play an important role in human detection as well as in scene understanding. The proposed method is based on the assumption that a person can exist again in an area where he/she existed in the past. In order to acquire the priors efficiently, a high prior probability is assigned to an area having the same color as past human trajectories. We use a particle filter for representing and updating the prior probability. Therefore, we can represent a complex prior probability using only a few parameters. Through experiments, we confirmed that our proposed method can acquire the prior probability efficiently and use it to realize highly accurate human detection. © 2010 Information Processing Society of Japan.