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Machine Learning/AI

Augmented Reality


Face Reframed is a series of wearable digital masks that explore the potential for post-human and grotesque representation in new and online contexts. Using biological imaging and a custom-trained machine learning model to generate the final works, Face Reframed seeks to decenter human aesthetics, blurring the boundaries between the digital, physical, symbolic, organic, human, and machine. 


By subverting traditional facial filters and upending expectations around human representation, Face Reframed rejects the idea that the human face should always be represented as a contained, idealized form. Instead it suggests that online, just like in life, we can inhabit a strange amalgamation of moving, changing, sometimes permeable parts.

Questions under artistic consideration:

What does the grotesque and post-human look like in online contexts?

Can biology be used to subvert traditional face filters and upend expectations around idealized human representation?

How might a machine learning-informed creative process help us decenter human aesthetics and reclaim power over our self-image? 

What does it look like to blur the boundaries between the digital. physical, symbolic, organic, human, and machine?

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Creative Process

Face Reframed was inspired by research into grotesque and post-human aesthetics, mainly how each art movement historically functioned as an antidote to Western concepts of idealized beauty. When I thought about modern spaces where idealized beauty was celebrated and perpetuated without challenge, augmented reality and facial filters came to mind. I envisioned a project that offered humans alternative filters they could "try on"  — a more imaginative, dynamic, and challenging way to envision identity in our digital era. 

In honor of the historically biological underpinnings of the grotesque, I began the project by collecting hundreds of images that related to anatomy, cellular structures, microscopic life forms, aging, and bodily fluids. Then, in an ode to the posthuman effort to blur the lines between human, nature, and machine I used those images to train a machine learning model, asking it to generate new images based on my input.

The generated results blurred the boundary between the human face and its anatomical underpinnings. I edited a selection of these works to make them suitable for facial filters and began to work with augmented reality tools to create a set of wearable "masks."

Once the filters were created on my desktop, I wrote a python script using computer vision to take the filter live. When I ran the script, it turned the laptop camera on, measured my facial dimensions and applied the filter. The grotesque masks were wearable in digital space.

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