Abstract :
Imagine Home surveillance cameras can monitor elderly parents and anticipate potential concerns while respecting their privacy.
Cameras can predict home burglaries based on suspicious behaviors, allowing time to notify the homeowner before the event occurs.
A network of cameras working together can keep an eye on neighborhood safety.
The cameras can also recognize and identify individuals and their behavior patterns, such as a delivery person dropping off a package.
The use of surveillance cameras raises ethical and privacy concerns and must be balanced with the need for safety and security.
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces.
About Application :
1.Safety and security are significant challenges facing modern society.
b. These issues aim to protect people's lives and valuable assets from illegal handling.
c. Safety and security extend to personal social security, protecting individuals' personal information, valuables, and daily activities.
d. This system can detect intruders in restricted or high-security areas and minimize human error.
e. The system uses algorithms and machine learning to identify and match facial patterns with a database of known individuals.
f. The system can provide real-time alerts to security personnel, enabling them to take appropriate action.
How to run this project ?
i. Keep harcascade File in the same folder.
ii. Download Install vgg_face_weights library (if needed)
iii. Install all dependecies (libraries)
iv. Run File index.py is to create the dataset and train the model at the same time.
v. Model data is trained and to validate the person is from home or not run file multithreading.py