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COMP5405: Digital Media Computing (2019 - Semester 1)

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Unit: COMP5405: Digital Media Computing (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: Dr Wang, Zhiyong
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Prohibitions: COMP5114 OR COMP9419.
Brief Handbook Description: 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 computer vision, autonomous car, drones, 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 for many cutting-edge digital media applications such as VR/AR. It will help students build practical computing skills for digital media driven applications and analytics, and utilise learned knowledge to produce creative and media rich solutions to real world problems.
Assumed Knowledge: COMP9103. Programming skills
Lecturer/s: Dr Wang, Zhiyong
Timetable: COMP5405 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Laboratory 1.00 1 11
3 Independent Study 6.00 13
T&L Activities: Lecture: Students are expected to attend all scheduled lectures.

Tutorial: Students are expected to attend all scheduled tutorials.

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Students develop technical solutions for project and homework. (1) Maths/ Science Methods and Tools (Level 4)
Students learn the fundamentals of multimedia data processing including acquisition, creation, analysis, compression and management and the state of the art in digital media in lectures. (2) Engineering/ IT Specialisation (Level 4)
Students develop solutions for assignment and projects. (3) Problem Solving and Inventiveness (Level 3)
Students perform functional design and revision to solve a specific problem by collecting requirements and applying the knowledge learned from this unit. (4) Design (Level 3)
Student complete project assignment by conducting informaiton collection, literature review, system design, report writing, and project presentation. (6) Communication and Inquiry/ Research (Level 4)
Students work in a small group to complet project assignment. (7) Project and Team Skills (Level 4)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table 2018.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(6) Communication and Inquiry/ Research (Level 4)
1. Explain multimedia processing and analysis techniques widely used in general scenarios
2. Peform research inquiry in a given digital media domain.
(7) Project and Team Skills (Level 4)
3. Develop basic project management and team coordination skills in a small group for completing a project.
(4) Design (Level 3)
4. Perform prototype design for a given task
(2) Engineering/ IT Specialisation (Level 4)
5. Explain the digitization of media data (e.g., image, video, and audio) in terms of acquisition and storage.
6. Perform the practice of processing and analysing on digital media data with specific techniques.
7. Reflect on the state-of-the-art digital media driven applications.
(3) Problem Solving and Inventiveness (Level 3)
8. Perform solution design for a given task.
(1) Maths/ Science Methods and Tools (Level 4)
9. Perform derivation of tehnical solutions for processing and analysing digitla media data and practical programming to implement the solutions
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Project Proposal Yes 10.00 Week 6 1, 2, 3, 4, 7, 8,
2 Project Final Yes 20.00 Week 12 1, 2, 3, 4, 6, 7, 8, 9,
3 Homework No 15.00 Multiple Weeks 1, 2, 4, 6, 8, 9,
4 Final Examination No 55.00 Exam Period 1, 5, 6, 7, 8, 9,
Assessment Description: * indicates an assessment task which must be repeated if a student misses it due to special consideration.

Text-based similarity detecting software (Turnitin) will be used for all text-based written assignments.

According to University`s assessment policy, late submission for assessment components other than Final Exam:

1) Assignments submitted electronically are to be consistently due at 23.59 on the submission day. For hard copy assignments/projects, you should naturally have a time during business hours.

2) Consistent penalty of 5% per day late.

3) Assignments more than 10 days late get 0.
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Minimum Pass Requirement 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.
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Other policies

See the policies page of the faculty website at for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar

Week Description
Week 1 Unit of Study Introduction
Week 2 Digital Media Basics
Week 3 Introduction to Digital Photography
Week 4 Digital Image Processing I
Week 5 Digital Image Processing II
Week 6 Digital Image Understanding
Assessment Due: Project Proposal
Week 7 Graphics and Animation
Week 8 Video Processing I
Week 9 Video Processing II
Week 10 Audio Processing
Week 11 Media Compression
Week 12 Project Presentations
Assessment Due: Project Final
Week 13 Course Review and Revision
Exam Period Assessment Due: Final Examination

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Graduate Certificate in Information Technology 2017, 2018, 2019, 2020
Graduate Certificate in Information Technology Management 2017, 2018, 2019, 2020
Graduate Diploma in Computing 2015, 2016, 2017, 2018, 2019, 2020
Graduate Diploma in Information Technology 2017, 2018, 2019, 2020
Graduate Diploma in Information Technology Management 2017, 2018, 2019, 2020
Master of Information Technology 2015, 2016, 2017, 2018, 2019, 2020
Master of Information Technology Management 2017, 2018, 2019, 2020
Master of IT/Master of IT Management 2017, 2018, 2019, 2020

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(6) Communication and Inquiry/ Research (Level 4) Yes 27%
(7) Project and Team Skills (Level 4) Yes 4%
(5) Interdisciplinary, Inclusiveness, Influence (Level 3) No 0%
(4) Design (Level 3) Yes 6%
(2) Engineering/ IT Specialisation (Level 4) Yes 41%
(3) Problem Solving and Inventiveness (Level 3) Yes 11%
(1) Maths/ Science Methods and Tools (Level 4) Yes 11%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.