A hybrid human fall detection scheme
Yie‐Tarng Chen, Yu‐Ching Lin, Wen‐Hsien Fang · 2010
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 feature and human shape variation, which can efficiently distinguish “fall-down” activities 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.