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Computer Aided Design, Manufacture and Engineering all rely on visual computing techniques such as computer graphics rendering and geometry processing.
Feature extraction and matching is a traditional method for shape matching and analysis.
This project intends to explore the combination of new techniques from related research areas and state-of-the-art SFS algorithms to improve robustness and feature preservation in shape recovery from single but sophisticated real-world image.
This project attempts to develop efficient techniques for the representation and matching of 3D shapes.
The captured either 2D or 3D data are usually unavoidably corrupted by imaging noise.
A low-discrepancy, blue-noise point set represents a continuous geometric object well, minimising discretisation artefacts.
3D surface registration is fundamental to many compute graphics, vision and medical applications.
This project explores how to create bas-reliefs from 2D face photographs.
3D models have a broad range of applications in many different areas such as engineering, biology, chemistry, medicine, entertainment and cultural heritage.
While the laser scanning systems usually have limited field of view, the captured data from a single viewpoint can only cover a part of the area of interest.