A video‐based human fall detection system for smart homes

In recent years, the global population has begun to age rapidly. Automatic fall detection for senior citizens has become an important issue for smart homes. This paper presents a novel video‐based human fall detection system that can detect a human fall in real‐time with a high detection rate. This fall detection system is based on an ingenious combination of skeleton features and human shape variations, which can efficiently distinguish “fall‐down incidents” from “fall‐like” ones. The experimental results indicate that the proposed human fall detection system can achieve a high detection rate and low false alarm rate.