Falls are a growing social problem and have become a hot topic in healthcare. Thanks to
recent advances in deep convolutional neural networks, the accuracy of video-based fall
detection has been greatly improved. However, these methods are affected by illumination
and complex backgrounds. Video angles and other influencing factors reduce the accuracy
and generalization ability of these methods. In this paper, a video-based human fall
detection method is proposed. First, a 2D joint point sequence in the video is extracted using …

Falls are a serious issue in society and have become a major topic in the healthcare
domain. Because of the rapidly increasing number of elderly people, falling can cause
serious consequences for the elderly, especially if the fallen person is unable to get up.
Early detection of falls and reducing waiting time help in saving the lives of the elderly. The
increasing number of cameras in our daily environment coupled with the presence of a
smart environment makes the vision-based system the optimal solution for fall detection …