Computer Vision and Image Analysis PG (8890.3)
|Available teaching periods||Delivery mode||Location|
|View teaching periods|| On-Campus
|| UC - Canberra, Bruce
|0.125||3||Faculty Of Science And Technology|
|Discipline||Study level||HECS Bands|
|Academic Program Area - Technology||Post Graduate Level|| Band 2 2021 (Commenced After 1 Jan 2021)
Band 3 2021 (Commenced Before 1 Jan 2021)
Learning outcomesOn successfully completing the unit, students will have a sound understanding of and will have gained hands-on experience in:
1. What computer vision and image analysis entails;
2. How images are formed and represented;
3. Understanding the basics of image processing and analysis techniques;
4. Understanding the concepts of fundamental theories in computer vision;
5. Writing Matlab programs for performing computer vision and image analysis tasks;
6. Being able to choose appropriate computer vision and image analysis techniques to solve real-world problems; and
7. Understanding the relationships between computer vision and image analysis on the one hand and fields such as perceptual psychology, digital signal processing, artificial intelligence and pattern recognition on the other hand.
Graduate attributes1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - communicate effectively
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - take pride in their professional and personal integrity
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
- 11376 Computer Vision and Image Analysis.
Assumed knowledgeWorking knowledge of discrete mathematics, algebra and numerical analysis.
|Year||Location||Teaching period||Teaching start date||Delivery mode||Unit convener|
|2021||UC - Canberra, Bruce||Semester 1||08 February 2021||On-Campus||Dr Roland Goecke|
|2022||UC - Canberra, Bruce||Semester 1||07 February 2022||On-Campus||Dr Roland Goecke|
Richard Szeliski, "Computer Vision: Algorithms and Applications", Springer, 2011, ISBN 978-1-84882-934-3
This book is available for purchase, for example, in the UC shop on campus. A limited number of copies of this book is also available from the UC Library.
Submission of assessment items
Extensions & Late submissions
Assessments are meant to be individual work, although talking a problem over with another student or tutor is considered one reasonable way of learning. However, the actual submitted assessment must be the student's own work. Students are expected to familiarise themselves with the University's Student Charter https://www.canberra.edu.au/Policies/PolicyProcedure/Index/200. Experience has shown that students who do not do their own work are unlikely to pass the exam (and therefore the unit).
Assessment submissions will be electronic through the Unit Website interface on UC Learn. For the Computer Vision Concepts Implementation assessment, students need to submit the their programming code and any additional files, such as images etc. to UC Learn. For the Student Colloquium Research Paper Presentation assessment, students need to submit all documents (presentation file(s) and research paper) that form part of their presentation to UC Learn.
Assessent submissions will be assessed for addressing the specific requirements of each assessment task, as stated in the assessment descriptions, as well as for employing good software engineering principles. Assessment submissions will receive a numerical mark, which together in their entirety with the other assessment items define a student's final grade as outlined in this section.
Extensions: Extensions must be applied for before the due date.
Students can apply for an extension to the due date for submission of an assessment item on the grounds of illness or other unavoidable and verifiable personal circumstances (extenuating circumstances). Documentary evidence will be expected in order that an extension be granted. Applications must be made in writing to the unit convener.
It should be noted that such documentation will be considered but will not guarantee that the application will be successful. The Unit Convenor will decide whether to grant an extension and the length of the extension.
Responsibility for understanding
If there is any doubt with regard to the requirements of any particular assignments or assessment procedure, the onus for clarifying the issue rests with the student who should contact the unit convenor or tutor. Further, it is the responsibility of students to ensure that they are correctly enrolled in the unit and that the tutor and Student Administration have their correct contact details.
Special assessment requirements
In CVIA PG, students are required to satisfactorily complete the Computer Vision Concepts Implementation and Student Colloquium Research Paper Presentation assessments (i.e. minimum 25% of available marks in each) and to perform satisfactorily in a final written exam. The Computer Vision Concepts Implementation assessment has a weighting of 35% and the Student Colloquium Research Paper Presentation assessment has a weighting of 25%. In addition, there will be three online tests in Week 4 (10%), Week 8 (20%), and Week 13 (10%).
To obtain a particular grade in this unit it is necessary that there are no outstanding submissions at the end of week 15. The unit convener reserves the right to question students orally on any of their submitted work.
All assessment items will receive a numerical mark. The final grade will be determined as a weighted average of the individual assessment items.
To be awarded a particular grade in CVIA PG, students must meet the overall requirements and any specific assessment requirements set out below. All grades are conditional upon the following minimum requirements:
- Minimum 25% of available marks in the Computer Vision Concepts Implementation, and
- Minimum 25% of available marks in the Student Colloquium Research Paper Presentation.
Minimum 50% of combined weighted marks of all assessment items
Minimum 65% of combined weighted marks of all assessment items
Minimum 75% of combined weighted marks of all assessment items
Minimum 85% of combined weighted marks of all assessment items
Refer to the Assessment Policy https://www.canberra.edu.au/Policies/PolicyProcedure/Index/488 and Assessment Procedures https://www.canberra.edu.au/Policies/PolicyProcedure/Index/545 for details.
There will be no supplementary or deferred tests.
Expected Average Student Workload: * denotes an assessable item
|Lectures||12x 1h||= 12h|
|Workshops||12x 1h||= 12h|
|Computer laboratory classes||12x 2h||= 24h|
|Preparation (lectures, tutorials, computer labs, reading)||12x 2h||= 24h|
|* Computer Vision Concept implementation||= 45h|
|* Student Colloquium Research Paper Presentation||= 18h|
|* Online Tests #1-3 (incl. preparation)||= 15h|
Total 150 hours
Your participation in both class (lecture, computer laboratory classes) and online activities will enhance your understanding of the unit content and therefore the quality of your assessment responses. Lack of participation may result in your inability to satisfactorily pass assessment items. Experience has shown that students who do not attend the classes and/or do not engage with the online content will have difficulty in passing the subject.
Required IT skills
Fundamental programming concepts, usage of Windows or Mac computers
Text book, 2x USB thumb drives and consumables
Work placement, internships or practicums
Not applicable to this unit
In all cases of absence, sickness or personal problems, it is the student's responsibility to ensure that the unit convenor is informed. The minimum participation requirement must be met in order to pass the unit (regardless of supporting documentation).
It is important that students refer to unit website (through UCLearn – UC's online learning environment) on a regular basis for any variations in the schedule and deadlines for the assessment tasks, which will be announced on the Unit Website. It is also the student's responsibility to ensure that they regularly check their UC email account, as electronic messages (whether via the unit's UCLearn site or directly) will be sent to this account.
The online discussion forum on the unit's UCLearn site is as very useful place for posting questions and students are strongly encouraged to make use of it.