Learning to Detect Touches on Cluttered Tables

04/10/2023

∙

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.

READ FULL TEXT

Learning to Detect Touches on Cluttered Tables

Web Table Extraction, Retrieval and Augmentation: A Survey

TabVec: Table Vectors for Classification of Web Tables

TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

A large-scale dataset for end-to-end table recognition in the wild

Generative Benchmark Creation for Table Union Search

Deep Learning-Based Computer Vision for Real Time Intravenous Drip Infusion Monitoring

Steganographer Identification

Learning to Detect Touches on Cluttered Tables

Related Research

Web Table Extraction, Retrieval and Augmentation: A Survey

TabVec: Table Vectors for Classification of Web Tables

TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

A large-scale dataset for end-to-end table recognition in the wild

Generative Benchmark Creation for Table Union Search

Deep Learning-Based Computer Vision for Real Time Intravenous Drip Infusion Monitoring

Steganographer Identification