On the Application of Egocentric Computer Vision to Industrial Scenarios

TL;DR

This paper investigates how egocentric wearable vision devices can be integrated into industrial workflows to improve data collection, annotation, and contextual understanding, potentially supplementing traditional machine vision methods.

Contribution

It introduces the application of egocentric vision in industrial scenarios, highlighting its potential to enhance data collection and contextual analysis in industrial settings.

Findings

Proposes a framework for egocentric vision in industry

Demonstrates improved data annotation processes

Provides resources for further research

Abstract

Egocentric vision aims to capture and analyse the world from the first-person perspective. We explore the possibilities for egocentric wearable devices to improve and enhance industrial use cases w.r.t. data collection, annotation, labelling and downstream applications. This would contribute to easier data collection and allow users to provide additional context. We envision that this approach could serve as a supplement to the traditional industrial Machine Vision workflow. Code, Dataset and related resources will be available at: https://github.com/Vivek9Chavan/EgoVis24