A HYBRID HUMAN FALL DETECTION SCHEME

被引：27

作者：

Chen, Yie-Tarng ^{[1
]}

Lin, Yu-Ching ^{[1
]}

Fang, Wen-Hsien ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei, Taiwan

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年

关键词：

fall detection; skeleton; human behavior analysis;

D O I：

10.1109/ICIP.2010.5650127

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：3485 / 3488

页数：4