- Adding LED's to the box which flash when a face is detected and recognized. This feedback would help you train and use the box without having to connect to the Pi in a terminal session.
- Make the main box.py script start up automatically when the Raspberry Pi powers on. Look at this blog post for more information on the various ways of automatically running a script at start up.
- Investigate using other face recognition algorithms in OpenCV. See the OpenCV tutorial on face recognition for more information. Algorithms such as Fisherfaces might be more robust to varied lighting or other conditions.
- Have the box send you an email with a picture of whoever is attempting to open it.
- Add a microphone and look at adding speech recognition as another means of unlocking the box.
This project is a great example of how to use the Raspberry Pi and Pi camera with OpenCV's computer vision algorithms. By compiling the latest version of OpenCV, you can get access to the latest and most interesting computer vision algorithms like face recognition. You can consider extending this project in other interesting ways, such as:This guide was first published on Jan 24, 2014. It was last updated on Jan 24, 2014. This page (Future Work) was last updated on May 04, 2015.