- Code ENGN6528
- Unit Value 6 units
- Offered by RS Electrical, Energy and Materials Engineering
- ANU College ANU College of Engineering and Computer Science
- Course subject Engineering
- Areas of interest Engineering
Computer Vision is an important field of Artificial Intelligence concerned with questions such as "how to extract information from image or video, and how to build a machine to see". Recent explosive growth of digital imaging technology, advanced computing, and deep learning makes the problems of automated image interpretation even more exciting and much more relevant than ever.
This course introduces students to fundamental problems in image processing and computer vision, as well as their state-of-the-art solutions. Topics covered in detail include: image formation, image filtering, camera geometry, thresholding and image segmentation, edge, point and feature detection, geometric frameworks for vision, single view and two views geometry; 3D visual reconstruction, camera calibration; stereo vision, image classification and object recognition, deep learning and neural networks for computer vision etc. The course features extensive practical components including computer labs and Term Research projects that provide students with the opportunity to practice and refine their skills in image processing and computer vision.
Upon successful completion, students will have the knowledge and skills to:
- Understand the foundations of modern computer vision theory, problem and state of the art solutions.
- Implement and test some fundamental computer vision algorithms e.g. image filtering, restoration, image segmentation, camera calibration.
- Analyse and evaluate critically the building and integration of computer vision algorithms and systems.
- Design and demonstrate a working computer vision system through team research project, and project report, presentation.
- Continue to critically review and assess scientific literature and apply the knowledge and skills gained from the course in developing innovative applications.
Professional Skills Mapping
Mapping of Learning Outcomes to Assessment and Professional Competencies
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Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
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|Class start date
|Last day to enrol
|Class end date
|Mode Of Delivery
|25 Feb 2019
|04 Mar 2019
|31 Mar 2019
|31 May 2019