Welcome!
This project was developed as part of a final year project for a bachelor's degree. The main objective of this application is to utilize computer vision to detect falls of elderly individuals using videos provided by home surveillance cameras.
The aging population in Algeria is steadily increasing, with individuals over 65 years old representing a significant portion of the population. Falls are one of the major issues faced by the elderly. The consequences of falls can be severe, leading to hospitalizations or even deaths.
In this context, this application employs computer vision to continuously monitor videos from surveillance cameras installed in the homes of elderly individuals. It detects potential falls and sends alerts to ensure their safety. Features
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Fall detection from surveillance videos.
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Utilization of computer vision techniques to analyze movements.
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Alert notifications upon fall detection.
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Run the "main.exe" file located in the Application/ folder.
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You can view the main code of the method used in the "code_main.py" file.
- Computer vision, Image and video processing.
- Python, OpenCV and PyQt for the GUI.
Any contribution to this project is welcome! If you'd like to add features, fix bugs, or improve documentation, feel free to submit a pull request or contact me.
If you find the repository informative and believe it could assist you in your projects, consider giving it a star ⭐️
This project was carried out as part of a bachelor's degree final year project. The application was designed to demonstrate fall detection from videos, and its effectiveness in a real production environment should be carefully evaluated.
Keywords: computer vision, video surveillance, fall detection.