COMP4405: Semester 1, 2023

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Units COMP4405 Semester 1 2023 [Normal evening]

Unit of study_

COMP4405: Digital Media Computing

Semester 1, 2023 [Normal evening] - Remote

Overview

Digital media data such as audio, image, videos, graphics, and 3D are increasingly becoming indispensable for big data driven computing applications in many domains, such as social media, public security, education, commerce, entertainment, and healthcare. This unit aims to bring students the essential knowledge on digital media, various computing techniques and tools on digital media processing and analysis, and many cutting-edge digital media applications such as VR/AR and Internet of Things (IoT) enabled new media. It will help students build practical computing skills for digital media driven applications and utilise learned knowledge to produce creative and media rich solutions to real world problems.

Unit details and rules

Unit code	COMP4405
Academic unit	Computer Science
Credit points	6
Prohibitions ?	COMP5405 or COMP5114 or COMP9419
Prerequisites ?	None
Corequisites ?	Enrolment in a thesis unit. INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103
Assumed knowledge ?	Experience with programming skills as covered in INFO1113 or COMP2123 or COMP2823 or INFO1105 or INFO1905 or other similar units
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Zhiyong Wang, zhiyong.wang@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Open book exam.	55%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Project proposal Group project proposal.	10%	Week 06 Due date: 27 Mar 2023 at 23:59	n/a
Outcomes assessed:
Assignment	Homework Submitted work.	15%	Week 08 Due date: 17 Apr 2023 at 23:59	n/a
Outcomes assessed:
Assignment	Project Final Group project final.	20%	Week 12 Due date: 15 May 2023 at 23:59	n/a
Outcomes assessed:

Assessment summary

Create one bullet point per assessment task, with a brief description that answers the question: 'What will a student be required to do?'.
Each item should not exceed 100 words, and details in the assessment table (e.g. weighting) should not be duplicated. Click ? icon for examples.
More detailed information (e.g. assessment rubrics) and submission instructions must be published on Canvas.
If the assessment table includes a hurdle task, students will see this statement on the unit outline: ‘Must meet the required standard in an assessment in order to pass the unit’. Please include brief details for students in the summary.
Add an additional note at the end: ‘Detailed information for each assessment can be found on Canvas.’

Assessment criteria

Assessment grading

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.

For more information see guide to grades.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

1. A statement regarding late penalties will display on the unit outline above any qualifying information you choose to include. Click the ? icon to see the statement. 2. Late penalties should be modified in accordance with the Assessment Procedures 2011.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Unit of study introduction	Lecture (2 hr)
Week 02	Digital media basics	Lecture and tutorial (3 hr)
Week 03	Digital image processing I	Lecture and tutorial (3 hr)
Week 04	Digital image processing II	Lecture and tutorial (3 hr)
Week 05	Digital image understanding 1	Lecture and tutorial (3 hr)
Week 06	Digital image understanding II	Lecture and tutorial (3 hr)
Week 07	Video processing	Lecture and tutorial (3 hr)
Week 08	Graphics and animation	Lecture and tutorial (3 hr)
Week 09	Digital image processing advanced I	Lecture and tutorial (3 hr)
Week 10	Digital image processing advanced II	Lecture and tutorial (3 hr)
Week 11	Media compression	Lecture and tutorial (3 hr)
Week 12	Project presentations	Lecture and tutorial (3 hr)
Week 13	Course review and revision	Lecture (2 hr)

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. explain multimedia processing and analysis techniques widely used in general scenarios
LO2. have developed basic project management and team coordination skills in a small group for completing a project
LO3. perform prototype design for a given task
LO4. explain the digitization of media data (e.g., image, video, and audio) in terms of acquisition and storage
LO5. perform the practice of processing and analysing on digital media data with specific techniques
LO6. reflect on the state-of-the-art digital media driven applications
LO7. perform solution design for a given task
LO8. perform derivation of technical solutions for processing and analysing digital media data and practical programming to implement the solutions.

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.

Included more content on image understanding.

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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