Dan O'Sullivan

You look at a screen that works as a mirror reflecting your face. If you blink your eyes, a picture of me thumbing my nose at you comes up but you will never know. Just like you will never know if your refrigerator light is really off. This was done as the Thursday project in the 7 projects in 7 days (5 in 5 for me, … er make that 3.5 in 5) festival at ITP. I am hoping to get back this afternoon to finish it but don’t know if I will.

I am looking for holes in the skin color to find the eyes. When I get back today I will segement out just the holes for the eyes.

Here is the code so far:

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Allows people to congregate in a layer on top of your web browser. Using a webcam attached to your computer the application grabs your face and sends it to other people looking at the same web page. Your face is displayed on other peoples’ browser at the place on the page you are most interested in as expressed by your cursor location. The web page becomes a substrate for gathering. In the future I would like to degrade the resolution of faces of people interested in things further away on the page and change to peer to peer architecture for the actual transmission of the images. This was done as the Thursday project in the 7 projects in 7 days (5 in 5 for me, … er make that 4 in 5) festival at ITP. (more…)

For determining the popularity of different video segments on public displays. It uses a camera and computer vision to notice how many faces are watching the screen. It takes advantage of a shortcoming of the OpenCV processing libraries for the face detection which only detect faces only at very limited angles. It it finds a face you can be assured that they are facing only the screen. Shawn Van Every created a video drop box for people to leave video to be seen on various screens around the floor. We wanted to be able to cull a best of list from the drop box so Shawn VanEvery and I thought face tracking might be interesting. It is currently hardwired to a particular video and only shows the “Attention Quotient” on the screen. If I had more time, I would integrate it with a database of videos and register the attention into that database. This was done as the Tuesday project in the 7 projects in 7 days (5 in 5 for me) festival at ITP.

Tech: I used IP cameras for the video capture. Below is the code:

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As people stand in front of a mirror, this applications uses face detection technology to find the faces in the video and then display them with just the faces switched. Each person looks normal except they have someone elses eyes, nose and mouth. This far I go before. In this excersize I wanted it to work for a crowd standing in front of the large screen display at IAC, Gehry building. This required that the faces be shared across multiple application so today I did the networking for that. If I had more time I would add an oval alpha mask so the faces blend better.  This was done as a Monday project in the 7 projects in 7 days (5 in 5 for me) festival at ITP.

Tech: I used the OpenCV processing libraries for the face detection. I used IP cameras for the video capture. Below is the code: (more…)