- Code ENGN6528
- Unit Value 6 units
- Offered by Research School of Engineering
- ANU College ANU College of Engineering and Computer Science
- Course subject Engineering
- Areas of interest Engineering
This subject extends students comprehension of the fundemental problems of computer vision and state-of-the-art solutions. Topics covered in detail include: image acquisition, sampling and quantisation; image segmentation, point, line and edge detection, and thresholding; geometric frameworks for vision, single view and two views; camera calibration; stereopsis, the correspondence problem and epipolar geometry; motion and optical flow; recognition, invariants, appearance and geometric-based identification; pose estimation in perspective images. The course includes an extensive practical component that provides the students with a tool box of skills in image processing and computer vision.
Upon successful completion, students will have the knowledge and skills to:1. Understand the foundations of modern computer vision theory, problem and state of the art solutions.
2. Implement and test some fundamental computer vision algorithms e.g. image filtering, restoration, image segmentation, camera calibration.
3. Analyse and evaluate critically the building and integration of computer vision algorithms and systems.
4. Design and demonstrate a working computer vision system through team research project, and project report, presentation.
5. Continue to critically review and assess scientific literature and apply the knowledge and skills gained from the course in developing innovative applications.
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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 summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|3170||15 Feb 2016||26 Feb 2016||31 Mar 2016||27 May 2016||In Person||N/A|