Human Fall Detection Using Video Surveillance

Authors

  • Kavya G Research Scholar, Visvesvaraya Technological University, Karnataka, India
  • Sunil Kumar C T Research Scholar, Visvesvaraya Technological University, Karnataka, India
  • Dhanush C Research Scholar, Visvesvaraya Technological University, Karnataka, India
  • Kruthika J Research Scholar, Visvesvaraya Technological University, Karnataka, India

Keywords:

Fall detection, video-based, Convolutional Neural Network, Elderly people, Smart home

Abstract

Fall is one of the biggest challenge in elderly people, pregnant and small children’s, who stays alone in home. Sometimes this fall leads to severe injuries and even to death. Detecting the fall is very much important for elderly people. Convolutional Neural Network (CNN) is an deep learning algorithm used for image processing. In this paper, we present a video-based fall detection using CNN, this CNN will perform background subtraction and captures only foreground objects to detect the human movements and detect if fall happens. Firstly, camera will be capturing all the movements of the person. Our proposed model will detect the fall and finally an alarm is raised and email is sent to a given particular caretaker and family member. Our experimental results show the best performance of the proposed model.

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Published

2021-03-12

Issue

Section

Articles