Are you passionate about bridging the gap between AI and real-world applications? Join us at the Lincoln Centre for Autonomous Systems (L-CAS) to work on an exciting project that utilizes computer vision techniques to enable advanced visual attention analysis of mobile eye-tracking footage.
In this project, you are going to develop a computer vision-based system that maps the gaze location along a sequence of images extracted from eye-tracking footage recorded with a mobile device (glasses) in a dynamic scene. The gaze mapping problem can be solved in a 2D (based only on image matching) or 3D (using SLAM or structure from motion) representation. In either case, the final goal is to generate a heatmap representation of the evolution of gaze positions within a specific time window.
You are expected to test the performance of your proposed system in footage from eye-tracking glasses worn by strawberry pickers working in controlled and real conditions.
Required Skills
- Strong programming skills in Python
- Good understanding of computer vision techniques
- Good understanding of Artificial Neural Networks
- Familiarity with Docker and GitHub tools
- Excellent communication abilities
Desirable Skills
- Familiarity with SLAM and/or structure from motion algorithms
- Familiarity with image matching algorithms
What We Offer
- Hands-on experience with cutting-edge AI technologies
- Integration into the dynamic L-CAS research team
- Possibility to participate in scientific writing and co-authoring a research paper
This is an internship position suitable for students pursuing a programme of study in computer science, robotics and/or AI at the University of Lincoln. If you are interested, fill out our Expression of Interest Form, choosing Dr Leonardo Guevara (lguevara@lincoln.ac.uk) as the researcher to supervise the project.