Testing Face Detection

As I looked into the face detection of processing I wanted to experiment if it worked with the face tracking for myself in which I found within the open CV library of processing in which i implemented below:


After finding out it actually works I realised it was perfect for my idea to become real giving me the motivation to still progress with my initial idea of the hand reaching out.

As open CV is a open source library it has given me this advantage of not figuring out the code for myself entirely, saving me the stress of not ripping my hair out therefore its allowed me more time to develop straight to me idea as my downfall is within code, however with the help of my peers and colleagues i was able to understand more of what code meant what.

It has come to my attention that by using face tracking focuses more on real-time images through processing as the way in which processing renders as I mentioned before works by taking images frame by frame, therefore it is far better than using the basic live feed of using a camera to just show a display of the person in front just like a webcam feature within existing programs like msn, facebook, skype and apples products facetime.

The way the face is tracked is through using the Cascade sheet that is already pre-loaded within the library as its programmed to use object detection in this case is the front part of the face using the code:

void setup() {

size( 640, 480 );

opencv = new OpenCV(this); opencv.capture( width, height ); opencv.cascade( OpenCV.CASCADE_FRONTALFACE_ALT );

// load the FRONTALFACE description file }

By knowing it does front face tracking only so far I needed to come across an approach of detecting the viewers head where it wasn’t facing the camera with still tracking there movement, as my idea consist of the viewer not becoming conscious of being watched while there heads are turned away from the screen through using the representation of online identity of social networking sites such as Facebook, instagram, twitter and lifestyle blogs.