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Computer Vision Museum

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Computer Vision Museum, 2020, (Installation View)


Four historically fundamental computer vision algorithms (“Real-time Face Recognition”,YOLO Object Recognition”, “Simple Blob Tracking” and “Polygon Filter”), displayed in real-time on interactive touchscreen tablets, accompanied by various historical ephemera related to the field of human vision and photography. Featuring: Four touchscreen tablets mounted in wooden frames, four embedded Logitech web cameras, an image viewer with interactive components, several historic analog cameras (in various stages of deconstruction), a lightbox, assorted photography ephemera, a Mansfield Model 950 8mm editor (augmented with modern physical computing hardware), mounted on a 10’ long, 5’ high table with four wooden columns for supports. A corkboard above features work produced from students during the workshops.

Exploring the media archeology of the digital camera as it relates to advances in the field of computer vision, I developed a miniature “computer vision museum” in conjunction with a series of workshops incorporating computer vision with a fine arts photography course.


As a collaboration with Virginia Tech photography faculty Michael Borowski, a series of workshops offered Fine Arts students a user-friendly introduction to the complexities of computer science; resulting in an exhibit exploring the intersection of computer vision technology and the fine art of photography.


The exhibit focused on a series of historic computer vision algorithms, each running in real-time & capturing the attention of passerby’s in the library. Each tablet-display encouraged interaction, demonstrating a video feed in real-
time overlaid with a range of signficant computer vision algorithms.

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Collaboration

For two weeks, Fine Art students were introduced to the foundations of OpenCV through a series of workshops.


Students learned how to track faces, track objects, and 3D scan themselves, resulting in student projects derived from experiments in computer vision, using OpenCV in the Unity Game Engine.

A History of Image Making

A timeline of image capture techniques, the exhibit contextualized the function of the digital camera with its ancestry in the history of image capture technology.


Showcasing historical visual media devices adjacent to each computer vision algorithm, the exhibit included vintage stereoscopes, camera obscuras, and various camera-related ephemera.

Events + Experiences

Our workshops resulted in an installation of modified interactive computer vision algorithms, paired with student work.


The exhibit included work by School of Visual Arts graduate and undergraduate students; featuring work by Amy Borg, Michelle Chen, Bobbie Daniels, Maddi Grainger, Paddy Huynh, George Jung, Zac Kim, Drew Nagle, Jessie Robinson, Jasmine Shah, & Ross Walter.