Geometric computing and graphics

Our group explores the design, capture, analysis and optimisation of 3D models and data, and their applications in computer graphics and other domains.

We live in a three-dimensional world. Modelling and processing 3D information is an important task in computer graphics and many other fields such as science, engineering, and architecture. The group works on fundamental techniques for 3D geometry processing including acquisition, registration, segmentation, optimisation, as well their real-world applications.

The group collaborates with the Welsh School of Architecture on the research and education of Computational Methods in Architecture.

Aims

Attracting PhD students and research funding
Facilitating cooperation with research groups and organisations outside the School of Computer Science and Informatics

Our research deals with two broad areas:

3D modelling and geometry processing techniques:

3D acquisition
3D reconstruction
surface parameterisation
shape registration
shape analysis
3D shape retrieval and indexing
data-driven modelling
procedural generation
numerical optimisation
mesh processing.

Applications of geometric computing:

3D printing
CNC machining
virtual and augmented reality
reverse engineering
robotics
architectural design
computer animation.

Selected publications

Qiao, Y. et al., 2022. Learning on 3D meshes with laplacian encoding and pooling. IEEE Transactions on Visualization and Computer Graphics 28 (2), pp.1317-1327. (10.1109/TVCG.2020.3014449)
Yang, S. et al., 2020. Noise-resilient reconstruction of panoramas and 3D scenes using robot-mounted unsynchronized commodity RGB-D cameras. ACM Transactions on Graphics 39 (5) 152. (10.1145/3389412)
Gao, L. et al., 2019. SDM-NET: deep generative network for structured deformable mesh. ACM Transactions on Graphics 38 (6) 243. (10.1145/3355089.3356488)
Zhang, J. et al., 2019. Accelerating ADMM for efficient simulation and optimization. ACM Transactions on Graphics 38 (6) 163. (10.1145/3355089.3356491)
Gao, L. et al., 2018. Automatic unpaired shape deformation transfer. ACM Transactions on Graphics 37 (6) 237. (10.1145/3272127.3275028)
Peng, Y. et al., 2018. Anderson acceleration for geometry optimization and physics simulation. ACM Transactions on Graphics 37 (4) 42. (10.1145/3197517.3201290)
Gao, L. et al., 2016. Efficient and flexible deformation representation for data-driven surface modeling. ACM Transactions on Graphics 35 (5) 158. (10.1145/2908736)
Konaković, M. et al., 2016. Beyond developable: computational design and fabrication with auxetic materials. ACM Transactions on Graphics 35 (4) 89. (10.1145/2897824.2925944)
Qin, Y. et al. 2016. Fast and exact discrete geodesic computation based on triangle-oriented wavefront propagation. ACM Transactions on Graphics 35 (4) 125. (10.1145/2897824.2925930)
Song, P. et al., 2016. CofiFab: coarse-to-fine fabrication of large 3D objects. ACM Transactions on Graphics 35 (4) 45. (10.1145/2897824.2925876)
Tam, G. K. L. et al., 2014. Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry. ACM Transactions on Graphics 33 (1) 4. (10.1145/2517967)
Tam, G. K. L. et al., 2013. Registration of 3D point clouds and meshes: A survey from rigid to nonrigid. IEEE Transactions on Visualization and Computer Graphics 19 (7), pp.1199-1217. (10.1109/TVCG.2012.310)
Wu, J. et al. 2013. Making bas-reliefs from photographs of human faces. Computer-Aided Design 45 (3), pp.671-682. (10.1016/j.cad.2012.11.002)
Wang, H. et al., 2013. Harmonic Parameterization by Electrostatics. ACM Transactions on Graphics 32 (5) 155. (10.1145/2503177)
Sun, X. et al. 2007. Fast and Effective Feature-Preserving Mesh Denoising. IEEE Transactions on Visualization and Computer Graphics 13 (5), pp.925-938. (10.1109/TVCG.2007.1065)

Project name: Deep Representations for Analysis and Reconstruction of 3D Shapes with Complex Structure and Rich Details
Funded by: Royal Society
Principal Investigator: Yukun Lai

Project name: Perceptual shape optimisation for 3D printing
Funded by: Royal Society
Principal Investigator: Yukun Lai

Project name: Computing canonical forms from collections of 3D models
Funded by: Royal Society
Principal Investigator: Paul Rosin

Project name: Efficient multi-resolution design for constraint-based modelling
Funded by: Royal Society
Principal Investigator: Bailin Deng