Camera-based system for tracking and position estimation of humans

Abstract

The human population is getting older and older, as stated by current studies. Because elderly people are at a higher risk of in house accidents there is an increasing need for ambient assisted living systems. These systems should detect accidents or dangerous situations in order to improve the quality of life for these people. The goal of this work is to build a robust and intelligent system which estimates the position of humans using only one camera. The position is used to detect falls and to allow an immediate call for help. The solution is based on a foreground-background-segmentation using Gaussian Mixture Models to first detect people and than analyze their main and ideal orientation using moments. This allows to decide whether a person is staying or lying on the floor. The system has a low latency and a detection rate of 88% in our case study.