Inspiration

We wanted to make an application that allowed for some modicum of privacy when looking at confidential information from prying eyes. This was the basis for our application.

What it does

It opens a privacy window when two people are looking at the computer, and has an anti-social mode that opens a window and shoots you call on your phone so you don't have to talk to whoever came up to you.

How we built it

We used a python backend that used OpenCV, an open source library for computer vision. Within OpenCV, we used EigenFaceRecognizer method to detect faces with reasonable accuracy. We then used this functional with HTML/CSS/Javascript powering the front end UI built with Electron to implement the goals of the Privacy Protector.

Challenges we ran into

We ran into some GUI obstacles by trying to make the GUI in C++ and found difficulties with making it in Electron due to inexperience among most of the team. Detecting faces instead of ceiling vents was easier said than done. Keeping our spirits high, and ourselves awake was a challenge.

Accomplishments that we're proud of

We're proud that we made a fully functioning GUI in Electron for our program, and got the AI to detect faces for the privacy window.

What we learned

Don't try to build a GUI in C++ How to use Tkinter for faster python development How to build nice looking interfaces with Electron Common facial recognition techniques, and strategies to improve recognition.

What's next for The Privacy Protector

Adding cross OS capabilities for the program. Although we have seperate versions that can run on every OS.

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