New Noise Machine Proposal

So, I have a completely new proposal for my sound machine, and I am very excited about this. For those of you who know about my artworks and the continual theme I have in creating art, you will have guessed that I want to make a noise machine that relates to food eroticism. Food eroticism is an important notion for me that illustrates the contemporary society’s unique trait in sensualizing food, in which relates to mass consumerism and advertising.

I wish to make a noise machine (more like a digital program) that can take food ads (e.g. McDonald’s Burger ads, front cover of Food Magazine) and transforming them into noises people make when they are eating. I want to use real people’s voices like “um, ahhh, nom”, preferably noises that can potentially be erotic.

 

Example “noises” would be something like: http://www.youtube.com/watch?v=wRF_lewLjAM

(This is my absolute favorite audio that I use over and over again in my artworks.)

 

How this program/machine would work is by taking the imagery of these advertisements, it generates a suggestive devouring noise based on the level of seductiveness of the advertisements. Mainly, the scale of eroticism would be based on the saturation of their colors.

 

I am fairly inexperienced with electronics and software, so my big question would be….
HOW CAN I EVEN MAKE THIS POSIBLE THROUGH MAX/MSP? 

 

 – Ruby 

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2 thoughts on “New Noise Machine Proposal

  1. You can use Jitter in Max to take an image from a webcam and extract the average amount of saturation by converting from RGB to HSL and averaging all the S components.

    That being said, if you use OpenCV (computer vision library used for stuff like facial recognition and object detection), you could be more ambitious and have the computer attempt to recognize different kinds of foods. You should also consider using Google’s reverse image search, eg using a picture of a stylized hot dog. This blog post explains how it can be automated.
    Unfortunately, both involves a tremendous amount of programming.

    Kinda irrelevant: http://impregg.herokuapp.com/
    (my team and I made this thing during a hackathon)

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