Augmented Vision - Applying Multiple Vision Styles to Industrial Contexts
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Overview
This PhD thesis explores how artificial vision styles can augment human perception in industrial contexts through Augmented Reality [4, 6, 7]. Modern sensors can capture information beyond natural human vision [1, 3, 5], including thermal, depth, and multispectral data. However, effectively presenting and combining these vision styles for human operators remains a major scientific and interaction design challenge.
The objective of this research is to design, implement, and evaluate interactive vision styles that enhance users’ perception and decision-making during industrial tasks such as maintenance, inspection, and object identification. Particular attention will be paid to situations where operators’ hands are occupied, ensuring that interaction remains efficient, intuitive and minimally intrusive [6]. The candidate will investigate how users can select, combine, and personalize vision styles, and how these augmentations influence task performance, cognitive load, usability, and user experience [2]. The work lies at the intersection of Human-Computer Interaction, Augmented Reality, and Computer Vision, and includes both technical development and experimental evaluation with human participants.
Expected outcomes include novel interaction techniques, design recommendations, and scientific contributions published in leading international conferences and journals in Human-Computer Interaction and Augmented Reality.
Context
ESTIA Research
ESTIA Research, an independent research unit affiliated with the University of Bordeaux (UPR RNSR 201420655V), is a multidisciplinary research team. Since 2009, all research activities at ESTIA have been consolidated into a single team called ESTIA Research, with an interdisciplinary focus at the interface of Science and Technology and Social Sciences and Humanities. ESTIA Research is dedicated to cutting-edge scientific and technological work. Its primary mission is to study, design, and implement Sustainable and Empowering Interfaces to enhance interactions between Human-Human, Human-System, and System-System. The results obtained are part of a dynamic transformation towards future industrial technologies and take into account energy transition and digital transformation.
Xibetek
Xibetek is a technological platform of ESTIA, dedicated to the Industry of the Future, located in Chéraute, in Soule. Associated with the Compositadour, Addimadour and Turbolab platforms, it is a center of expertise dedicated to advanced technological solutions, specializing in robotic laser stripping, multi-technology additive manufacturing, and robotics/cobotique applied to industrial environments.
Objectives
- Conduct a comprehensive literature review on vision augmentation, augmented reality, and interaction techniques.
- Design and implement multiple interactive vision styles using AR technologies.
- Develop an Augmented Reality interface allowing users to select, combine, and customize vision styles.
- Implement prototypes using appropriate technologies (e.g., Unity, AR headsets, sensing technologies).
- Design and conduct controlled user studies involving human participants.
- Perform statistical analysis of experimental data.
- Iteratively improve the system based on experimental findings.
- Publish research results in international peer-reviewed conferences and journals.
- Present findings at scientific conferences.
- Write and defend a PhD thesis.
Requirements
- Master’s degree (or equivalent) in Computer Science, Human-Computer Interaction, Engineering, or related field.
- Strong motivation for research and willingness to learn.
- Strong interest in Human-Computer Interaction, Augmented Reality, and Computer Vision.
- Programming experience (e.g., Python, C#, Unity, or similar).
- Interest in experimental research involving human participants.
- Ability to work independently and within a research team.
- Good written and spoken English.
- Experience with Augmented Reality, Unity, or user studies is a plus but not mandatory.
Application
Candidates should send a CV, motivation letter, academic transcripts, and any relevant projects or publications to w.delamare@estia.fr and n.couture@estia.fr. Please also provide contact information for two references. Review of applications will begin immediately and continue until the position is filled. Shortlisted candidates will be invited for an interview (remote or in-person depending on the candidate’s location).