High-fidelity Deformable Object Simulation (SUSTech candidates only)
This project is available as part of the Leeds-SUSTech Split-Site PhD Programme.
High fidelity fabric/cloth simulation has been a central topic in several fields ranging from computer animation, visual effects to fashion design and fabric manufacturing. Although many simulation methods have been proposed, one often finds it difficult to choose the right simulator because there is still a lack of good metrics to quantitatively compare simulated and real fabrics/cloths. The difficulties come from three facts. First, fine-grained simulations are often painfully slow due to complex collision detections and a large physical model. Second, usually the physics is empirically modelled and has little or no room for calibration based on data. Finally, there is a lack of good way to collect accurate fabric/cloth deformation data. The key to the solution is a physical model that is amicable to parallel computing and collision detection while has the freedom to be tuned based on data observations. This is the goal of this PhD project. In addition, new quantitative evaluation methods will also be proposed. Finally, the research will lead to the design of a common evaluation tool i.e. a benchmark program for collision detection of deformable objects.
Applications are invited from candidates with or expecting the minimum equivalent of a UK upper second class honours degree (2:1), and/or a Masters degree in computing or related discipline. If English is not your first language, you must provide evidence that you have English language proficiency of at least IELTS 6.5 with no component below 6.0, or equivalent.
How to apply
Applications should be submitted via SUSTech in the first instance. Following nomination by SUSTech, formal applications for Split-site research degree study should then be made online through the University of Leeds website. Please state clearly in the research information section that the PhD you wish to be considered for is ‘High-fidelity Deformable Object Simulation (SUSTech candidates only)’ as well as Dr He Wang as your proposed supervisor.
If you require any further information please contact the Graduate School Office
e: firstname.lastname@example.org, t: +44 (0)113 343 8000.