Project Info

Virtual Tattoo (VT)

Inspiration

The stories of survivors of fire accidents broke our hearts when we heard about the challenges they had to face even after their narrow survival. Not just burn victims but all victims with scars they are afraid of struggle with the choice of whether to conceal them with tattoos. We believe emerging AR technology can facilitate this dilemma with an easy hand gesture to save them from their troubles.

What it does

Our system facilitates users with scars visualize how their body would look with the tattoo that they want to apply. Using the AR technology of Snap Spectacles, with a flick of their wrist, users can see the transformation of their scars to beautiful tattoos.

How we built it

Using the Spectacles Interaction Kit(SIK) we edited the Hand Visuals to have tattoo designs applied accordingly following simple hand gestures. Using a script written in javascript we were able to add a condition that detects the user's hand angle to trigger tattoo applications.

Challenges we ran into

Snap Spectacles is a very new emerging product that is a few weeks old. The lightweight and user friendly hardware has a lot of potential to be used in daily lives. However it requires additional solutions to compatibility issues with current lens studio versions, library imports and api adaptations in order for applications to work smoothly.

Accomplishments we're proud of

We made the best out of the remaining time we had to create a working product as we realized the limits of the technical possibilities we became aware of as we attempted several experiments on ASL sign language adaptations, web api applications, and customizations of current lens studio components.

What we learned

We realized the need to get more familiar with the limits of Snap Spectacles to effectively customize and apply external technologies. Also because of the innovative nature of Spectacles, even the simplest ideas and design can be effective.

What's next

for VT To introduce realtime generative ai and audio/visual detection applications using ML to our product.

Analysis

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Metric

sqkimofficial
2

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

JavaScriptIn code
TypeScriptIn code

2 of 2 appear in the indexed code.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

1.4 MB

Source files

166

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.