The concept that I settled on was to make a system that allowed users to interact with the Hunt Swiss Poster collection, an extensive set of extraordinary Swiss design posters that are housed in the Hunt Library which very students know exist. Originally, I had planned on using the Kinect to allow users to “draw something” using a colored depth map that would then get processed to display the closest Swiss design poster. However, in my early protoyping, it was starting to get apparent that the interaction was not as obvious as it could be, which was leading to a weaker installation. Moreover, as I have had to borrow all of my equipment from IDeATe for every project, I ran into the issue that every Kinect and my specific computer was checked out for the time span that I needed to work on this project. Therefore, I had to pivot.

While planning the projection installation, we were hit with the news that the Kinect was no longer going to be produced. As I was forced to work without a Kinect anyway, I decided to work on creating an interesting interaction with just an RGB camera which thankfully will probably always be produced. Additionally, I realized that, although being a far more difficult path, the best possible way for users to interact with these Swiss posters was to be a literal part of them, which would mean every single poster would have to be designed uniquely. However, this direction would also result in an avenue where several students could choose to participate in this project if they are lacking in their ideas for projects.

Therefore, for my Project 2, I created two different Swiss poster exhibits as well as a very simple UI that an IDeATe staff member would use when turning on the projection system each morning. Each exhibit has an interaction display that mimics a Swiss poster design that is placed next to the original Swiss poster, some information about the poster, and some information about the project.

First Exhibit: 

Second Exhibit: 

UI Snapshot: 

Gist of Code: 

Video of the system working:

Gist of code: https://gist.github.com/anonymous/9ddab8deb04b40090d8efeb8cd0b5f06

For this example video, I simply used ambient noise as a catalyst (people walking by and talking) as I’m interested in making renderings that will use ambient noise/images from an environment in a way that is obvious yet still interesting. Unfortunately, the Youtube compression ruins the effect quite a bit, but the general visual is preserved. A Google Drive link to the video is located here: https://drive.google.com/open?id=0Byn46tolhCwUUlNzNDVObGppY1k

Github Gist Here: https://gist.github.com/anonymous/f69fd0c33650aeab618f81ad8d37ecfe
*** When I tested the compressed code just for checking to make sure my file was all right, for some reason the rendering just stays stationary while on my actual code it is working fine. For this reason, I also am uploading a zip file of my files, just in case something messed up on the copy compressed feature for some bizarre reason.
Zip of Files: Assignment 4 – Sarika Bajaj

Original Audio Clip (Dobby is Free):

My two acoustic space IR recordings were taken by recording the audio of a balloon popping (with its accompanying reverb). The locations I chose to record were the women’s bathroom in the basement of Baker hall and the overlook present on the second floor of Baker Hall.

IR from Women’s Bathroom in Baker Basement:

Convolution of Dobby and Women’s Bathroom IR:

IR from Overlook in Baker:

Convolution of Dobby and Overlook in Baker:

I then explored a little bit of what the Dobby recording would sound like when convolved with common soundtrack noises that might be present in a bad movie. Specifically, I chose gurgling water, seagulls cawing, applause, and crickets soundtracks that I downloaded from SoundBible.com.

Gurgling Water IR:

Convolution of Dobby and Gurgling Water:

Seagulls IR:

Convolution of Dobby and Seagulls:

Applause IR:

Convolution of Dobby and Applause:

Crickets IR:

Convolution of Dobby and Crickets:

After making these samples, I started exploring some of the built-in Max examples and ran into one named “convolution workshop.” A bit curious about what it would do, I merged our original convolution reverb patch this patch. Specifically, I pushed the “Dobby is free” audio and the “applause” IR through the original convolution and then pushed the result into a source filter convolution with the “Dobby is free” audio again. The result sounds significantly more noisey than the previous results.

Further convoluted Dobby and Applause:

The final Max patched used to create the last audio piece can be found here: https://gist.github.com/anonymous/37367ee3fca07b4a057610ee7ff6630d

Depending on whether particle interaction, shape manipulation, etc. is easier for me to bring up, I might pivot the project more to one of those directions. However, as a minimum, I would like to be able to create a system that creates a live time interactive piece with the Kinect and Max.

Gist of code: gist:6f11dc358eabb3a5d7dc3f2dba39f493

As I have been recently setting up my new townhouse, I thought I would start with a simple search on Amazon for “office chair.” I then recorded the first suggested item of the list and then clicked on it to create the chain. If I encountered a situation where the suggested item looped, I simply recorded the next in line suggested item that I had not previously clicked on and continued down the chain. I followed the chain to about 50 items, by which time I had not seen an office chair for quite a while.

The video of the path across Amazon is below: