On the Application of Egocentric Computer Vision to Industrial Scenarios
This work addresses data collection challenges in industrial settings, but it appears incremental as it builds on existing egocentric vision concepts.
The paper explores using egocentric wearable devices to enhance industrial data collection and annotation, potentially supplementing traditional machine vision workflows.
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