About This Project
This research project focuses on developing a computer vision-based fall detection system specifically designed for elderly care. Falls are one of the leading causes of injury among the elderly population, and early detection can significantly improve outcomes.
The system utilizes deep learning technology, specifically Convolutional Neural Networks (CNN), combined with background subtraction techniques. These methods are highly capable of detecting human presence and analyzing body posture to identify fall events in real-time.
The implementation processes video feeds to continuously monitor for fall patterns, triggering alerts when a fall is detected. This allows for immediate response from caregivers or emergency services, potentially saving lives.