Following my recent posts (one two three) about my Sentiment Enforcement exhibition piece, I figured I’d do a brief write-up about the completed (albeit occasionally buggy) piece and explain the work now that it is finished, as well as link the resources that I used so that you can do face detection too! Be sure to check out the twitter account linked to this piece that I will explain later on in the post;

Ministry For Sentiment Enforcement Twitter Account

In my first post about the piece I explained the general premise of the design and theory behind it following my research report. The piece, as I explained in this post, is designed to play on the notions that in a world where technology is prevalent in cities and our homes we are never far from legal judgement. Even today we face constant threats of spying and surveillance by our own governments, so this idea of being constantly and continuously judged by the authorities is not unfounded.

The piece uses facial detection software written in python using haarcascading (sorry for the techy bits) to detect the viewer’s face through the use of a live webcam feed. Since my last posts I have changed the styling of the piece completely as you can see below, to one which I feel mirrors the more 21st century feeling of surveillance rather than my previous attempt at a more Soviet-esque style iconography.

The piece then alerts the viewer that they must smile, or else face unknown consequences. The smile detection is also done using haarcascading in a similar way to the face detection, but with different detection patterns. When smiling, the user must hold their smile for a set amount of time, or else fail.

And then once scanned, the user is told that they are compliant and allowed to carry on…

…or else they fail and are alerted to the fact that they have been marked for arrest and logged in a database…

…which takes the form of a twitter account that the program uploads their photo to in order to simulate the . The twitter account follows the theme of the program nicely;

The exhibition will take place on Monday-Wednesday, so the piece is not officially finished until it is in the gallery and running smoothly with no errors and with people viewing. I’ll do another writeup for that when the time comes but for now it’s back to the debugging to make sure it is as spick and span as I can possibly make it in time for the gallery.

Here is the list of resources I used when building the backbone of my face detection program;

Don’t forget to install OpenCV and Numpy

http://opencv.org/downloads.html

http://docs.opencv.org/trunk/doc/py_tutorials/py_objdetect/py_face_detection/py_face_detection.html

https://realpython.com/blog/python/face-recognition-with-python/

https://realpython.com/blog/python/face-detection-in-python-using-a-webcam/

http://coding-robin.de/2013/07/22/train-your-own-opencv-haar-classifier.html

