For my typology machine, I want to capture human exhalations of air while performing everyday gestures whose air patterns are invisible to the naked eye. To do this, I plan to utilize schlieren imaging. The study would consist of at least 3 participants being asked to laugh (prompted by viewing a funny video), whistle, cough, sigh, and yell. The final form would be an animated side by side GIF collage of each of the air patterns.
I’d like to use the eye tracker to reveal the sequence that people look at images. When looking at something, your eyes move around and quickly fixate on certain areas, allowing you to form the impression of the overall image in your head. The image that you “see” is really made up of the small areas that you’ve focused on, the remainder is filled in by your brain. I’m interested in the order in which people move their eyes over areas of an image, as well as the direction that their gaze flows as they look.
Eye tracking has been used primarily to determine the areas that people focus on in images, and studies have been conducted to better understand how aspects of images contribute towards where people look. In this example, cropping the composition changed how people’s eyes moved around the image.
There is also a famous study by Yarbus that showed that there’s a top-down effect on vision; people will look different places when they have different goals in mind.
I haven’t been able to find any studies that examine the sequence in which people look around an image. I’d like to see if there are differences between individuals, and perhaps how the image itself plays a role.
I’m going to show people a series of images (maybe 5) and ask them to look at each of them for some relatively short amount of time (maybe 30 sec). I’ll record the positions of their eyes over the course of the time in openFrameworks. After doing this, I’ll have eye position data for each of the images for however many people.
Next, it’s a question of presenting the fixation paths. I’m still not totally sure about this. I think I might reveal the area of the image that they fixated on and manipulate the “unseen” area to make it less prominent. There’s lots of interesting possibilities for how this might be done. I read a paper about a model of the representation of peripheral vision that creates distorted waves of information.
It could be nice to apply this kind of transformation to the areas of the image that aren’t focused on. The final product might be a video that follows the fixation points around the image in the same timescale as they’re generated, with the fixation in focus and area around distorted. A bit like creating a long exposure of someone’s eye movements around an image.
Experiences with the normally hidden aspects of our body can feel peeled out of a thriller film. We may find ourselves in a small, white room with a stranger examining us with a cold instrument. We don’t know whether we’ll be okay. Images are flashed on screen for a few seconds, a diagnosis made, a fate delivered. A sense of disconnect. This is a script for a experiencing a sonogram.
Taken out of this medical context, the sonogram can become a tool for portraiture. Nevertheless, entertainment, or “keepsake” ultrasounds have historically been discouraged by the FDA, particularly for creating images of fetuses:
use of ultrasound solely for non-medical purposes such as obtaining fetal ‘keepsake’ videos has been discouraged
In some states, sonograms for entertainment are even illegal (though not the state in which this project is being created).
However, there is value in re-encountering the heart outside of a medical context. Contact with hidden parts the body can become, as opposed to an experience of fear, can be one of joyful exploration. We can observe our hearts moving with rhythm and purpose; a thing of beauty. Conversely, we can appreciate the weird (and meaty) movement that is (nearly) always there with us. A collection of hearts help us explore diversity in this motion. This project asks: what similarities and differences in the motion of the heart can be seen between people via sonogram?
The Machine
I am reaching out to my familiars, taking their portraits casually in a private space. I chose to capture the parasternal long axis view of the heart-one Hearts will be annotated with structure labels in motion.that is easily accessible and produces a semi-legible cross section:
Hearts will be annotated with structure labels in motion. These are the structures visible in the parasternal long axis view with the sonogram device available:
As an ensemble, this is what multiple hearts captured with the sonogram look like:
Some inspiration
It looks like Memo Atken is getting into medical imaging with these MRI videos ostensibly processed with some kind of machine learning:
For my typology machine, I’m going to look at my contact lenses!
fun!
I have worn contacts since I was 8 years old, so there’s plenty of questions I could come up with (for example, how many daily pairs have i worn in my entire life? What is the amount of packaging waste I’ve generated through this? Yikes.)
They’re a really cool material to play with – transparent, squishy, very different wet/dry textures, etc. For the purpose of this assignment, it’s an awesome opportunity to experiment – what can I capture about this material that I have never been able to see otherwise?
My machine will look at them between polarizingfilters, using a DSLR, macro lens and light table.What kind of surface tensions are there on different pairs? How much does each lens differ from the next? (despite quality standards, there’s an occasional lens that is not the right shape. What does this look like?) What does an inside-out lens look like, compared to one that’s right-side-out? If I look at every pair I wear for a week, how does each day differ? Does a fresh lens look different from one I’ve been wearing all day?
example of polarizing filters to see surface tensions in transparent objects. Source: https://www.lockhaven.edu/~dsimanek/TTT-polaroid/TTT-polaroid.htm
It’s a pretty simple concept, which is fine by me and leaves opportunity for some fun discoveries & experimentation.
Beyond just using polarizing filters, what other things could I capture about my contact lenses? For example, is there some way to “see” how dirty they are at the end of the day? I’m open to suggestions and excited to get started.
My plan for the typology project is to explore the phenomenon that has tried to be defined by many names but I am calling “Anti-ASMR” (as referenced to by some on the internet). It will take the form of a video compilation of terrible sounds, and possibly (if I have time) a compilation of people’s reaction to these sounds.
Names and definitions some people associate with this:
Misophonia: (Not what I am studying, but related) is a disorder in which certain sounds trigger emotional or physiological responses that some might perceive as unreasonable given the circumstance. Those who have misophonia might describe it as when a sound “drives you crazy.” Their reactions can range from anger and annoyance to panic and the need to flee. Misophonia may cause a reaction to sounds such as dripping water, chewing, snapping gum, or repetitive noises, such as pencil tapping.
Hyperacusis: (Not what I am studying, but related-ish) Not specific to a certain sound is a highly debilitating rare hearing disorder characterized by an increased sensitivity to certain frequencies and volume ranges of sound (a collapsed tolerance to usual environmental sound). A person with severe hyperacusis has difficulty tolerating everyday sounds, which become painful or loud. Hyperacusis is often associated with autism.
Grima (Spanish term that is exactly what I’m exploring): Great article putting into words this feeling
But although grima is most often associated with sounds, some participants said grima was triggered by the feel of certain objects – as foam rubber does for Schweiger. Some were objects associated with loud noises, but others were objects that don’t make noise, such as cork, velvet or sponges.
I think it is fascinating that we don’t have a word for this in English which is an obvious sign that this phenomenon lacks a lot of research. Most projects that I have seen that are similar to my idea (like this video) contain sounds that almost everyone finds somewhat annoying/disgusting. What sets this typology apart from others is the fact that most of these sounds except one or two don’t bother me personally at all. However, I know that many of these actions are largely despised among groups of people even though the subject is rarely talked about. I think I find it so fascinating because it is like we all have our own personal kryptonite of which we share with certain individuals (for example, my sister and I share a trigger but we don’t share it with our parents). Also, I think there’s something wonderful in the fact of discovering we are not alone in these weird repulsions many of us have. Therefore, I am planning to record a compilation of sounds and textures of mundane things that commonly give people a negative physical reaction in order to better study this phenomenon.
To do this I plan to record myself making many of these unpleasant sounds using both the binaural microphone for audio in order to simulate texture and the way humans hear such sounds and a DSLR camera to highlight the texture in the objects themselves. The actions will be filmed in a plain, ideally white, and, well lit area that has no background noise. Only the hands of the person performing the action will be shown. The objects and actions mentioned are gathered from sources from my personal social media, word of mouth, and from online sources such as Reddit.
Symptoms People Have Said They Experience:
Shivers
Goosebumps
Have to bite their tongue
Tongue swell up
Gagging
Repulsive reaction
Feeling of “makes me want to turn inside out” “makes me feel like my teeth are going to fall out.” “My nerves are trying to burrow out of my body”
Thinking about these triggers is enough to feel them
What Sounds/Textures I Plan to Record:
Unpolished dry wooden spoons against dry skin
Nail files on nails
Styrofoam against Styrofoam
Styrofoam against cardboard
Styrofoam against Felt
Scratching Styrofoam
Scratching Vinyl/3D Folders
Water bottle with ridges (especially when wet)
Glossy photos (like for the dole show) scraped against nails
For this assignment I plan on measuring the population density of different rooms on campus. Such information would provide us with how crowded certain rooms are during the day and what rooms people tend to prefer at what times. This app also has applications in assisting people trying to find free rooms for studying.
The “machine” for this project would be a pressure plate that is configured at the entrance of a room in front of the door. When people walk into or out of the room, the pressure plate would detect the footstep of the person. The problem then arises as to whether the pressure denotes an ‘enter’ or ‘exit’ movement. Since most people walk with the back of their foot hitting the ground before the front, then the direction of pressure would indicate the type of movement.
This information would then be sent to a computer which would visualize the data. A translucent building schematic with red dots would indicate the presence of people in a room. While we would not know the exact location of these people in the room, we would still know the population density, which is useful for estimating which rooms are crowded at what times. Ultimately this resource can give students and staff an average indication as to when what rooms are free and/or have available working spaces, while also giving us information to multiple questions such as:
Do people enter alone or in crowds?
What times of the day are rooms most crowded? Most free?
How long on average does a person spend in a room?
Are people making frequent trips out of the room? Are they sitting in place for a long time?
The inspiration for this project was mostly from spy movies where they would use a translucent grid to track people with red dots (The above image is from a video game [Jedi Fallen Order] but has the same premise). The idea sounded really unique, and I wanted to see how well I could emulate this given just a computer and pressure plate.
