School of Computer Science and Statistics
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
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
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
How we move through a crowd is influenced not only by where other people are, but also by how we perceive them. This project will investigate whether the appearance and proximity of virtual people influence how users behave when navigating through a crowd in Virtual Reality. The student will develop a VR crowd environment in … Read more
This project aims to enhance the visual diversity and realism of crowds in real-time virtual environments by combining AI-driven texture generation for clothing with procedural variation techniques applied to a limited set of template MetaHumans in Unreal Engine. By leveraging state-of-the-art AI models to generate diverse, high-quality clothing textures dynamically, the project will create varied … Read more
[FYP] In this project, you will improve the realism of emotion on Metahumans in Unreal Engine by developing a realistic tear system, where tears are affected by gravity, and smudge in contact with make-up for added realism. Also part of the project will be motion capturing crying animations, and evaluating the resulting emotion with and … Read more
[FYP or MSc Level] This project will explore how lighting design, informed by cinematography and psychological theories, can be used to enhance emotional expressivity in characters and user immersion within a real-time VR open-world environment. The student will research emotional lighting techniques from film and psychology—such as color theory, contrast, and lighting direction—and apply them … Read more
[MSc level] Virtual assistants are becoming commonplace but the ability for them to gesture naturally and appropriately is still a huge research challenge (see image which shows a typical assistant displayed from the neck up, without gesturing arms and hands). In this project, you will develop a method to automatically learn structure from speech sequences … Read more
[FYP or MSc Level] This project will investigate clothing a virtual character using existing cloth plugins (e.g. uDraper or Marvelous Designer), and applying them to photorealistic Metahuman characters in UE5. Cloth simulation will then be tested using Chaos cloth or other, and student will create an embodiment system, where the user can embody a character … Read more