School of Computer Science and Statistics
Rachel McDonnell 
Can we tell something about a person from the way they move, even when their appearance has been completely changed? In this project, the student will use selected interactions from Meta’s Seamless Interaction dataset to create animated MetaHuman characters in Unreal Engine 5. Real conversational motion will be transferred onto virtual characters whose appearance differs … Read more
How do two people coordinate their movement, gaze, gestures and speech during a conversation, and what can these behaviours tell us about the social interaction taking place? In this open-ended project, the student will use Meta’s Seamless Interaction dataset, a large-scale multimodal dataset of face-to-face interactions containing processed body motion, facial behaviour, gaze, audio, speech … Read more
Eye gaze plays a fundamental role in face-to-face communication, signalling attention, engagement, turn-taking and social intent. However, gaze is often studied from the perspective of only one participant. This project will create a new dataset of synchronised eye movements from pairs of people engaged in natural social interactions, using two wearable Pupil Labs eye-tracking headsets. … Read more
The voice of a virtual human is a powerful cue to its identity, personality, age, emotion and social characteristics. Psychological research on cross-modal face–voice perception suggests that people have expectations about which voices belong with which faces. People can make associations between unfamiliar faces and voices, while characteristics such as vocal pitch, apparent age, femininity/masculinity, … Read more
In Virtual Reality, strong embodiment is usually achieved by making an avatar closely reproduce the user’s physical movements. But what happens when the virtual body does not move in the same way as the real body? Can haptic feedback help users accept unfamiliar virtual movements as their own? In this project, the student will develop … Read more
Imagine visiting a virtual museum as a family after closing time, where the exhibits have mysteriously come to life and an AI-driven virtual museum guide needs your group’s help to discover what has happened. This project will develop a short multiplayer VR experience for 3–4 players, in which a MetaHuman guide dynamically responds to the … Read more
Virtual crowds typically rely on a limited set of motion-capture clips, which can lead to visible repetition and reduce the perceived diversity and realism of the crowd. This project will investigate whether Epic Games’ new AnimGen generative animation framework can be used to create more varied and individualised motion for virtual crowds. The student will … Read more
Creating Virtual Reality experiences normally requires specialist software and significant programming experience. This project will investigate how web-based 3D and generative AI tools can make VR creation accessible to children, allowing them to create a 3D world in a browser and then immediately experience it inside a VR headset. The student will develop a child-friendly … Read more
People perform the same actions in subtly different ways, creating an individual motion signature. This project will investigate whether these characteristics are preserved—or lost—when human motion is learned by a generative animation model. Using Epic Games’ new AnimGen framework and the HiPHI motion-capture dataset, the student will select a small number of performers performing similar … Read more
Recent generative animation models can create realistic character motion rather than simply replaying existing animation clips. In this project, you will use Epic Games’ new AnimGen framework and motion-capture data from the large-scale HiPHI dataset to investigate human-object interaction. The student will select a manageable subset of interactions, such as approaching, reaching for, picking up … Read more