Outline

Overview

This unit provides a broad introduction to the field of graphics and multimedia computing to meet the diverse requirements of application areas such as entertainment, industrial design, virtual reality, intelligent media management, social media and remote sensing. It covers both the underpinning theories and the practices of computing and manipulating digital media including graphics / image, audio, animation, and video. Emphasis is placed on principles and cutting-edge techniques for multimedia data processing, content analysis, media retouching, media coding and compression.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	COMP2123 or COMP2823 or INFO1105 or INFO1905
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Programming skills
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Weidong Cai, tom.cai@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final exam Restricted open book exam	60%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Creative work	Assignment-1a multimedia computing 1a	8%	Week 08 Due date: 28 Sep 2025 at 23:59	n/a	AI allowed
Outcomes assessed:
Creative work	Assignment-1b multimedia computing 1b	8%	Week 11 Due date: 26 Oct 2025 at 23:59	n/a	AI allowed
Outcomes assessed:
Creative work	Assignment-2 graphics and multimedia applications	16%	Week 13 Due date: 09 Nov 2025 at 23:59	n/a	AI allowed
Outcomes assessed:
Practical skill	Lab checkpoints take-home exercise submission based on specified lab exercise content	8%	Weekly	n/a	AI allowed
Outcomes assessed:

Assessment summary

Lab checkpoints: weekly lab exercise submission;

Assignment-1a&-1b: multimedia computing;

Assignment-2: graphics and multimedia applications;

Final exam: restricted open book exam.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction / Image data representation and enhancement	Lecture (2 hr)
Week 02	Morphological image processing	Lecture (2 hr)
Week 02	Computing Lab with LCP	Tutorial (2 hr)
Week 03	Color models & color image processing	Lecture (2 hr)
Week 03	Computing Lab with LCP	Tutorial (2 hr)
Week 04	Video data representation and processing	Lecture (2 hr)
Week 04	Computing Lab with LCP	Tutorial (2 hr)
Week 05	Audio data representation and coding	Lecture (2 hr)
Week 05	Computing Lab with LCP	Tutorial (2 hr)
Week 06	2D & 3D computer graphics	Lecture (2 hr)
Week 06	Computing Lab with LCP	Tutorial (2 hr)
Week 07	Computer animation and multimedia authoring	Lecture (2 hr)
Week 07	Computing Lab with LCP	Tutorial (2 hr)
Week 08	Image data analysis and retrieval	Lecture (2 hr)
Week 08	Computing Lab with LCP	Tutorial (2 hr)
Week 09	Advanced visual content analysis	Lecture (2 hr)
Week 10	Video data analysis and retrieval	Lecture (2 hr)
Week 10	Computing Lab with LCP	Tutorial (2 hr)
Week 11	Image coding and compression	Lecture (2 hr)
Week 11	Computing Lab (assignment help session)	Tutorial (2 hr)
Week 12	Video coding and compression	Lecture (2 hr)
Week 12	Computing Lab (assignment help session)	Tutorial (2 hr)
Week 13	Advanced multimedia computing	Lecture (2 hr)
Week 13	Computing Lab (assignment help session)	Tutorial (2 hr)

Attendance and class requirements

Tutorials: Students are expected to attend all scheduled on-campus tutorials.
Independent Study: Students are expected to undertake prescribed reading and practical work, besides understanding lecutre contents. 6 hours of independent study per week is expected.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. apply multimedia data processing and analysis techniques to real world applications
LO2. understand data representation and enhancement for different multimedia building blocks
LO3. understand various multimedia data coding and retrieval techniques
LO4. obtain practical skills in graphics / image, audio, and video processing and analysis.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No significant changes have been made since this unit was last offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

COMP3419: Graphics and Multimedia

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links