GMU:Max and the World/Felix Geith: Difference between revisions

The goal of the semester project was to write a Max Patch for an interactive sound installation.  

The data, that's gained from the video tracking is used to influence the parameters of the sound as well as the spatialisation of the sound, meaning its position in the room. This already offers quite a lot of potential to give the recipient a feeling of influence on his environment.

The whole process of planning, building and testing the installation happened during the first online semester and Covid-19 pandemic. Most of the life of an ordinary student such as me happened in a small room. Wether it’s working, sleeping, resting, meeting a few friends or just spending free time, everything that normally happened in quite different spaces was now forced and compressed into a small room. That naturally created different areas and spaces with very different meanings, actions and emotions connected with them. They often clashed, yet it wasn’t that easy to separate them from each other. These smaller areas are the basis for the sound composition.  

This also meant, that the installation was meant to be placed in a normal bedroom of a students flat, instead of a studio room. On one hand this meant that a speaker setup had to be placed in this room, on the other hand it meant that the sound quality wouldn't be as nice as in a professional surround studio. Yet, the environment wouldn't be fitting the context and idea of the installation, if it was placed in an "artificial" surrounding like a surround studio.

To be independent from the light condition in the room, an infrared camera was used. The most practical, and especially cheapest way to do this was using a Kinect 360 camera.  

As you can see on the pictures above, the kinect camera was hung to the ceiling facing downwards.

Right here you can find a video documentation of the final installation prototype. The audio signal will be explained, recorded and converted to stereo. Like this the audio isn't spatialized, but at least you are able to hear it.

https://youtu.be/70AmTmC-R4E

I will add a video about the patch very soon!

So, if you put up the camera on the ceiling and shoot from above, the normalisation will only allow the Kinect to record the object that's the closest, in this case the head of the person in the room. The "jit.findbound" then only sees the head on the video, and determines its position in realtime. Like this you can track the position of the recipient in the room.

'''SOUND MATERIAL'''

'''HARDWARE'''

2: '''Kinect Input and normalisation''' https://www.youtube.com/watch?v=ro3OwWnjfDk&list=PLG-tSxIO2Jkjj0BthZ_y0GRkWRjAvL1Uo&index=5

The project so far is finished and came to an end. Yet, the patch, and the installation context will be developed further, as there is a huge potential in this instrument.