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POUR is an AR application that estimates a container’s volume using only a smartphone camera and shows the fill height for a user-specified amount of content.

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https://github.com/boostcampaitech8/pro-cv-finalproject-cv-06

Project at a Glance

The Problem

People often need to know either the total capacity of an unmarked container or the correct fill height for a specific amount of content (especially when cooking). Doing so normally requires a measuring cup or another calibrated tool.

POUR explored a more convenient alternative: scan a cup or similar container with a smartphone, reconstruct its shape, estimate its volume, and visualize the requested water level in AR.

This required more than predicting a single capacity value. To display the fill height for any requested amount, the system needed to estimate cross-sectional area at different heights and integrate those areas into a volume profile.

Project Direction

As Project Director, I organized and led team meetings, defined the experimental direction, and coordinated parallel development across two application architectures. I also designed experimental reconstruction pipelines and proposed optimization strategies, including segmenting and masking containers in the input images to reduce unnecessary 3D-reconstruction work.

My Core Contributions

• Founded the team and directed a four-person project from concept to prototype.
• Facilitated technical discussions and aligned the team around measurable product goals.
• Designed experimental pipelines combining segmentation, multi-view depth estimation, and 3D reconstruction.
• Proposed using 2D segmentation masks to limit reconstruction to the container region and reduce processing cost.
• Evaluated the trade-offs between server-based and fully on-device inference.
• Investigated TSDF and mesh-based reconstruction as an experimental branch.
• Helped frame the product around both total volume and height-specific volume estimation.

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The TSDF and mesh pipeline was an experimental direction that I designed and tested. Because of the one-month schedule, it was not used in either final application. Both completed apps reconstructed point clouds, detected circular cross-sections at multiple heights, and integrated those areas to estimate volume.

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Two Parallel Architectures