Learning to Detect Touches on Cluttered Tables
This work addresses the challenge of enabling interactive digital experiences on everyday tables for users, though it appears incremental as it builds on existing camera-projector tabletop systems.
The authors tackled the problem of making cluttered tabletop surfaces interactive by developing a real-time, on-device learning-based touch detection algorithm, achieving robustness to clutter as a key limitation of existing systems.
We present a novel self-contained camera-projector tabletop system with a lamp form-factor that brings digital intelligence to our tables. We propose a real-time, on-device, learning-based touch detection algorithm that makes any tabletop interactive. The top-down configuration and learning-based algorithm makes our method robust to the presence of clutter, a main limitation of existing camera-projector tabletop systems. Our research prototype enables a set of experiences that combine hand interactions and objects present on the table. A video can be found at https://youtu.be/hElC_c25Fg8.