Computer Vision

Cod y Modiwl
CSM4220
Teitl y Modiwl
Computer Vision
Blwyddyn Academaidd
2027/2028
Semester
Semester 1
Cyd-gysylltydd y Modiwl
Professor Bernard Tiddeman
Rhestr Ddarllen
Gweld ar Aspire
Rhagofynion

Previous programming experience
Anghymharus (Unrhyw Flwyddyn Acad)
CS34020
Can't take PG version if you've already done UG version.
Staff Eraill sy'n Cyfrannu

Dulliau Asesu

Math o Asesiad

Manylion Asesiad

Cyfran
Asesiad Semester Assignment: 30 Awr 50%
Arholiad Semester Written Exam: 2 Awr 50%
Asesiad Ailsefyll Supplementary written assignment: 30 Awr 50%
Arholiad Ailsefyll Supplementary Exam: 2 Awr Will take the same form, under the terms of the Department's policy. 50%

Canlyniadau Dysgu

Wedi cwblhau'r modiwl dylai'r myfyrwyr fedru:

  1. Express a consolidated and extended understanding and knowledge of Computer Vision techniques.
  2. Compare, critically evaluate and discuss competing methods.
  3. Explain the problems, techniques and difficulties associated with the different areas of Computer Vision.
  4. Critically evaluate existing research in Computer Vision, and demonstrate how this research may be applied appropriately to alternative application areas.

Disgrifiad cryno

The module will introduce the subject of Computer Vision with applications in a variety of contexts, including robotics, security and image analysis. It will start with low-level vision such as edge detection, feature detection, and segmentation. Intermediate vision will describe various techniques to infer 3 dimensional information from images. Some high-level techniques will be introduced, leading to discussion of deep learning approaches.

Nod

The aim of the module is provide a grounding in applied computer vision, including real-time and low-level techniques through to high-level and deep learning approaches. It is intending to prepare students for projects and employment opportunities utilising computer vision techniques.

Cynnwys

Foundations of vision: Image acquisition, sources of noise, human visual perception, and the evaluation and design of visual computing systems.

Edges and features: The image as landscape, edge detection, feature detection and representation, appearance as feature.

Motion: The video as a 3D dataset, feature tracking, background subtraction, modelling motion and change.

Objects: Grouping features, grouping motion, modelling variability. Learning models.

3D: Shape from X (shading, defocus, occlusion, photometric stereo). Multiview techniques (binocular, structure from motion). Direct 3D capture techniques (lidar, sonar).

Deep learning: Convolutional neural networks, attention mechanisms and Transformer architectures, generative networks, loss functions and training schemes.

Sgiliau Modiwl

Math o Sgiliau

Manylion Sgiliau
Cyfathrebu Exam writing develops written communication skills
Datblygu personol a chynllunio gyrfa There is a substantial demand for computer vision expertise.
Datrys Problemau Problem solving is intrinsic to computing in general.
Gwaith Tim This module will require individual rather than team work.
Gwella dysgu a pherfformiad ei hun Independent learning is necessary to complete the module
Rhifedd Computer vision involves higher level mathematical concepts
Sgiliau pwnc penodol Computer vision.
Sgiliau ymchwil This is a research driven module; research skills will be exercised throughout
Technoleg Gwybodaeth Information and communications technology is intrinsic to computer science.

Nodau

Mae'r modiwl hwn yn cydymffurfio a FfCChC Lefel 7