KF6019 - Advanced Computer Vision

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What will I learn on this module?

This module provides you with the opportunity to explore state-of-the-art technologies and research work in advanced computer vision. You will learn about key topics in Computer Vision, such as object and scene recognition, action recognition, active learning for image / video retrieval, motion and tracking, 3D reconstruction and segmentation.

In particular, the module will cover the following topics:

1. Visual Features including Colour Features, Shift Invariant Fourier Transform, Local Binary Patterns, Space-time interest points (STIP)
2. Object and Scene Recognition including Clustering, Bag-of-Words Model, Gaussian Mixture Model, Machine Learning for Vision
3. Human Action Recognition using Effective Codebooks and Tracking
4. Face Identification and Verification
5. Object detection, tracking and categorisation
6. Video analysis and understanding

Due to the research-based nature of the module, you will employ and extend you experience of key research skills (e.g. using literature, using citation, critical analysis, and evaluation) throughout the module.

How will I learn on this module?

Lectures will introduce you to theories related to the main topics. The lectures will be informed by recent research work in advanced computer vision, including from international conferences in Computer Vision such as CVPR, ICCV and ECCV. During lectures, you will be encouraged to ask questions and also engage in interactive activities to aid your understanding.

You will be provided with practical exercises in workshops. These will give you opportunities to practise and explore relevant techniques covered in the lectures and will include working with Matlab.

How will I be supported academically on this module?

The module team will guide and support you in the lecture and practical sessions. During the lectures, you will be required to conduct interactive activities based on the lecturers’ guidance. The module team will prepare diverse examples of real-life applications to support you in learning complex Computer Vision techniques. The module team will work closely with you in the practical sessions to conduct discussions, provide further detailed guidance on the subjects covered and to provide you with feedback on your work.

You can also request appointments with the module teaching team outside of scheduled class time to ask questions and seek advice.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:
1. Demonstrate critical knowledge and understanding of advanced computer vision techniques and identify state-of-the-art developments in the field.
2. Implement Computer Vision Algorithms


Intellectual / Professional skills & abilities:
3. Apply Computer Vision techniques to solve real-world problems
4. Evaluate the effectiveness of implemented computer vision applications

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Demonstrate research skills in the construction of project reports and the presentation of products.

How will I be assessed?

Summative assessment
The module will be assessed by one individual assignment (50%) and one group assignment (50%).

For the individual assignment, you will write a critical evaluation of and prepare and deliver a presentation on, a research paper from a Computer Vision conference, such as CVPR, ICCV and ECCV. This will assess MLOs of 1, 3, 4 and 5.

In the group assignment, you will work in a team to practise your knowledge and skills by creating and evaluating a computer vision application from a list of given topics. This will assess MLOs of 1, 2, 3 and 4.

You will be provided with written, electronic, feedback for each of the summative assignments.

Formative assessment and feedback
The exercises in the practical sessions provide opportunities for formative assessment, helping you and your tutors to assess your progress. You will receive guidance and ongoing feedback on your work and progress verbally in lab sessions.

You will also have the opportunity to discuss your progress and the needs of the summative assessment informally in the practical class sessions.

Pre-requisite(s)

None

Co-requisite(s)

None

Module abstract

This module provides you with the opportunity to explore state-of-the-art technologies and research work in advanced computer vision. You will learn about key topics in Computer Vision, such as object and scene recognition, action recognition, active learning for image / video retrieval, motion and tracking, 3D reconstruction and segmentation.

What will I learn on this module?

This module provides you with the opportunity to explore state-of-the-art technologies and research work in advanced computer vision. You will learn about key topics in Computer Vision, such as object and scene recognition, action recognition, active learning for image / video retrieval, motion and tracking, 3D reconstruction and segmentation.

In particular, the module will cover the following topics:

1. Visual Features including Colour Features, Shift Invariant Fourier Transform, Local Binary Patterns, Space-time interest points (STIP)
2. Object and Scene Recognition including Clustering, Bag-of-Words Model, Gaussian Mixture Model, Machine Learning for Vision
3. Human Action Recognition using Effective Codebooks and Tracking
4. Face Identification and Verification
5. Object detection, tracking and categorisation
6. Video analysis and understanding

Due to the research-based nature of the module, you will employ and extend you experience of key research skills (e.g. using literature, using citation, critical analysis, and evaluation) throughout the module.

Course info

UCAS Code G400

Credits 20

Level of Study Undergraduate

Mode of Study 3 years full-time or 4 years with a placement (sandwich)/study abroad

Department Computer and Information Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2020

Fee Information

Module Information

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