So, for my final project I’d like to revisit my music paintings from the chance-based system project.
My color algorithm was a happy accident. However, it only incorporated a small section of the frequency spectrum.
My initial experiments of utilizing the full frequency spectrum resulted in very muddy images. And unfortunately, I ran out of time, so I went back to my previous algorithm.
For my final project, I would like the resulting colors in the paintings to carry more meaning. I would like to be able to answer questions concerning the color. Like, why are ZZ Top’s music paintings primarily purple? What characteristics in the song cause it to be so?
To do this, my first step will be taking a closer look at the FFT graphs of songs over time. This will allow me to see what is the actual input I’m using in my color function, giving me a better understanding of what is happening. I also have a very loose understanding of sound and FFT analysis. I feel like studying this would also give me a greater comprehension of the technical aspect of music.
I found a paper entitled “Time-frequency Analysis of Musical Rhythm” by Xiaowen Cheng, Jarod V. Hart, and James S. Walker. I haven’t really read through it quite yet, but one of the diagrams seemed very applicable.
To help keep myself on track, here is a projected schedule of what I’m planning on doing each week till the final project presentation.
- Create various spectrograms of contrasting/similar songs (See former post for song choices).
- Begin analysis of spectrograms
- Test prints of existing color algorithms (considering varying scales and types of paper).
- Start composing new color algorithm based on correlations found in spectrograms.
- Tweak line density/thickness/opacity depending on test prints.
- More test prints using new line distribution.
- Finalize color algorithm/line distributions from previous week testing.
- More test prints for color matching.
- Create ideal gallery floor plan.
- Final prints.
- Final video.