Measurement and estimation of indoor human behavior of everyday life based on floor sensing with minimal invasion of privacy

摘要

This paper describes a method of measurement and estimation of human behaviors in a room together with the layout of objects on the floor. The information obtained by the method is essential for a service robot working in a human daily life environment. The method uses only one laser range finder (LRF) installed in the room and a strip of mirror attached to a side wall close to a floor. The area of sensing is limited to a plane parallel to and just a few centimeters above the floor, thus covering the whole room with minimal invasion of privacy of a resident while reducing occlusion. Processing both distance and reflectance acquired by the LRF from the surface of the existing objects allows us to exclude immediately distinguishable clusters and to focus on the analysis of remaining clusters. The human behavior models that we propose are effectively used to estimate human behavior based on the limited LRF data. Our experimental results validate the effectiveness of the proposed method.