Inspiration

We were inspired to use computer vision with AR to improve the experience of shopping for furniture. We hope to ease the furniture shopping process by providing guidance in determining which furniture items suit the overall color scheme of a room.

What it does

Furniture ARt uses image processing to suggest possible furniture options. Then shoppers can visualize what the piece of furniture would look like in their home using Furniture ARt's augmented reality feature.

How we built it

There are two components to the code: the image processing view and the AR view. The views were built separately and were combined at the end.

Challenges we ran into

We spent a lot of time going over the basics of Android Studio in order to bring all members to a sufficient skill level that would allow full team involvement in android app development. We also spent several hours trying to get the AR Core API to utilize Wayfair's 3D models, which was a struggle for members who had never touched APIs before. At times we felt like giving up, but we persisted and triumphed.

Accomplishments that we're proud of

It took us about 12 hours to figure out how to make a Wayfair chair to show up in AR, and while we didn't end up using that code, we were quite happy when we saw the chair on the screen for the very first time. We were also super excited when our app was able to select different assets based on the RGB values that we calculated.

What we learned

Two members of the team _ learned how to use Android Studio for the very first time. _ One member had never programmed in Java before. As a team, we learned how to integrate Google's AR Core into our applications.

What's next for Furniture ARt

In the future, we hope to improve the UI of the application. We also hope to integrate a bin-sorting method, expanding the options of the app to match a wider range of colors, not just compare RGB values.

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