Statistics have shown that most fall events are associated with identifiable risk factors, such
as weakness, unsteady gait, medication use, and the environment. Falls can result in …

More than thirty percent of persons over 65 years fall at least once a year and are often not
able to get up again. The lack of timely aid after such a fall incident can lead to severe …

In this paper, we present a human fall detection method from visual surveillance. In first step,
background subtraction is performed using Improved GMM to find the foreground objects. In …

We propose a novel computer vision based fall detection system using deep learning
methods to analyse the postures in a smart home environment for detecting fall activities …

Deaths from accidental falls are the second leading cause of mortality from nonfatal injuries.
Over the past two decades, there has been an explosion in research into the possibility of …

This paper presents a novel fall event detection method based on the motion vector and
accumulated image map. The proposed method consists of the following steps; i) human …

Automatic human fall detection plays a significant role in monitoring senior citizens.
Detecting fall events in an intelligent indoor condition can be used as a medium to reduce …

In this paper, we propose a novel and robust fall detection system by using a density method
for modeling a fall event as a function of certain video feature. 3-D head velocity and human …

Automatic detection of human fall events is a challenging but important function of the real-
time surveillance system. The goal of the proposed system is to develop a frame-by-frame …

An increase in population of elderly people living in isolated environments, leads to the
need for an automated monitoring system. Fall is one of the major reasons for death of …