Aims:

To expose students to the challenges and potential of geometry processing in relevant application areas. To explain how to use acquire 3D model, and subsequently process, analyse, and manipulate the data. To familiarize students with handling real data sets and apply machine learning algorithms in the context of 3D geometric data.Learning outcomes:

On successful completion of the module, a student will be able to:

Read and understand recent advancements in this area (theory).
	Obtain a grasp of the key tools in geometry processing (theory) and understand current machine learning approaches in the context of geometry processing.
	Gain necessary coding and practical skills to work directly with real-world 3D data (practice).
	Learn to formulate and solve problem using the geometric tools they learn as part of the module (practice).
Content:

The module introduces basics of geometry processing covering important aspects of acquisition, analysis, and manipulation of 3D data. The module will consist of a mix of theory and applications to real-world scenarios.

The module intends to introduce students to the various stages of a typical geometry processing pipeline. With the recent growth in popularity of 3D acquisition devices (e.g., depth cameras) and modeling frameworks, geometry processing now plays a central role in a diverse set of applications including city planning, architectural geometry, reverse engineering, interactive modeling, etc;

Topics will include but not restricted to mesh representations, mesh smoothing, remeshing, mesh reconstruction, and shape analysis. Necessary topics in differential geometry will be covered in the module.

Introduction:

Applications.
	Surface representations.
Geometry Registration:

Local and global registration (ICP, branch-and-bound).
	Geometry Acquisition.
	3D acquisition using laser scanners.
	Structure from motion-based acquisition.
Differential Geometry:

Introduction to curves and surface.
	Introduction to curves and surface.
	Mesh Smoothing and Decimation.
	Parametrization and Remeshing.
	Mesh Deformation.
	Laplace Beltrami Operator.
	Shape Analysis.
	Shape Synthesis.
	ML in the context of geometry processing.
Requisites:

To be eligible to select this module as an option or elective, a student must: (1) be registered on a programme and year of study for which it is a formally available; (2) should have an understanding of linear algebra; and (3) have coding experience.