You will carry out experiments using high fidelity immersive virtual reality to explore the way that people represent 3D space. You will learn psychophysics techniques and will be introduced to analysis techniques for discriminating between computational models of 3D scene representation.
Department: Psychology
Supervised by: Andrew Glennerster
Our lab focuses on theories about how the brain represents 3D scenes as the observer moves around. Currently, there are very different types of models: one type assumes that the brain generates a 3D model of the scene (either centred on the observer or fixed relative to the word, “allocentric”). Another type of model assumes that the brain “knows” about the way that images change as the observer moves but does not do this by building a 3D model. Modern neural network approaches are of the second type. The UROP projects would be part of a larger effort to distinguish between these two types of models. We will recruit participants that will be asked to explore a realistic indoors scene in VR. They will use a head mounted display and their head will be tracked as they walk. Specifically, participants will start at one location of the scene (‘home’) and they will then be transported virtually to a different location. This will allow us to investigate how moving observers can return to the previously visited location (home) from the new location while they will without simply remembering the image they were first shown. Data collected from this experiment will be used to compare various models, such as 3D reconstruction maps generated by Simultaneous Localization and Mapping (SLAM) algorithms. The student will be actively involved in data collection, analysis and interpretation of results.
The student will help recruit participants and run experiments. They will help participants carrying out tasks in virtual reality (using a head mounted display). The student will be involved in data collection as well as data analysis. The student will also be expected to advance his/her knowledge in the field through reviewing relevant literature. The student will receive hands on training from the supervisor on all aspects of the project. The level of involvement in analysis will be, to some extent, up to the student.
The student is expected to show enthusiasm for the project and keenness to learn. The student should, preferably, have a good understanding of statistics while experience with MATLAB is desirable but not necessary.
The student will have the opportunity to gain experience with Virtual Reality and develop transferable skills on data analysis and programming (MATLAB, C#). Furthermore, the student will have the opportunity to receive training on software such as Unity Game Engine and develop their knowledge on psychophysical experiments. Finally, the placement could, potentially, lead to co-authorship on a publication.
The student will be provided with a desk space and PC access within the School of Psychology and Clinical Language Sciences.
Regular office hours
Monday 21 June 2021 - Thursday 30 September 2021
The post will be advertised centrally on the UROP website until 9th April 2021. Students should submit their CV and Cover Letter directly to the Project Supervisor (click on supervisor name at the top of the page for email). Interviews will be held by Prof Andrew Glennerster.