Note: This unit is an archived version! See Overview tab for delivered versions.

COMP9419: Digital Media Fundamentals (2016 - Semester 1)

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Unit: COMP9419: Digital Media Fundamentals (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.
Brief Handbook Description: Digital media data such as audio, image and videos are increasingly becoming indispensable for big data driven computing applications in many domains, such as social media, public security, remote sensing, education, commerce, entertainment, and healthcare, to name a few. Knowledge on digital media computing has been essential for the booming job market on data science and data analytics. This unit aims to help students build up practical computing skills with digital media, and gain basic understanding of digital media data. It introduces the basics of digital media programming, the fundamentals of digital media data acquisition, processing, analysis, 3D graphics, and animation, as well as cutting-edge digital media applications.

[Students studying other degrees can also be enrolled in this unit by applying for special permission.]
Assumed Knowledge: None.
Lecturer/s: Dr Wang, Zhiyong
Timetable: COMP9419 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 1.00 1 11
3 Independent Study 6.00 1 13
T&L Activities: Tutorial: Students are expected to attend all scheduled tutorials.

Independent Study: Students are expected to undertake prescribed reading and practical work besides understanding lecture contents

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 need to apply the knowledge learned from this unit to solve a specific problem in related areas. Design (Level 3)
Students will learn the fundamentals of multimedia data processing including acquisition, creation, analysis, compression and management and the state of the art in digital media. Engineering/IT Specialisation (Level 3)
Students will gain practical experiences in processing multimedia data. Maths/Science Methods and Tools (Level 3)
Students will gain capacity for exploring their interests from related literature. Information Seeking (Level 3)
Students will practice their writing and oral presentation skills. Communication (Level 3)
Students have to organise themselves on how to most effectively fulfill the task as a team. Project and Team Skills (Level 3)

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

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.

Design (Level 3)
1. Apply learned knowledge to solve problems.
Engineering/IT Specialisation (Level 3)
2. Understand multimedia fundamentals: data sampling and quantization in acquisition.
3. Understand image/audio/video processing techniques.
4. Understand audio/image/video compression techniques.
5. Understand the popular and the-state-of-the-art of multimedia applications.
Maths/Science Methods and Tools (Level 3)
6. Obtain basic practical skills in multimedia data processing.
Information Seeking (Level 3)
7. Obtain skills in exploring interests in the digital media domain.
Communication (Level 3)
8. Obtain the basic capacity to articulate multimedia processing techniques and present applications.
Project and Team Skills (Level 3)
9. Obtain project management and team coordination skills
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Review No 5.00 Week 3 (During your timetabled class, 6 pm) 5, 7, 8,
2 Project Proposal Yes 7.00 Week 6 (During your timetabled class, 6 pm) 1, 2, 3, 4, 5, 7,
3 Quiz* No 10.00 Week 7 (During your timetabled class) 1, 2, 3, 4, 5,
4 Project Final Yes 18.00 Week 12 (During your timetabled class, 6 pm) 1, 2, 4, 5, 6, 7, 8, 9,
5 Lab Skills No 10.00 Week 11 (During your timetabled class, 8 pm) 1, 2, 3, 4, 5, 6, 7,
6 Final Exam No 50.00 Exam Period 1, 2, 3, 4, 5, 6, 8,
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.

Late submission for assessment components other than Quiz, Lab Skills, and Final Exam:

1) There is no penalty for submissions until 11:59pm of the due day.

2) Submissions which are late than 11:59 of the due day will be given ZERO marks.
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 IT 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 Introduction to Digital Media Computing
Week 3 Digital Media Acquisition
Assessment Due: Review
Week 4 Introduction to Digital Photography
Week 5 Digital Image Processing (I)
Week 6 Digital Image Processing (II)
Assessment Due: Project Proposal
Week 7 Object Recognition
Assessment Due: Quiz*
Week 8 Graphics & Animation
Week 9 Video Processing
Week 10 Audio Processing
Week 11 Digital Media Compression
Assessment Due: Lab Skills
Week 12 Project Presentation
Assessment Due: Project Final
Week 13 Unit of Study Review and Reflection
STUVAC (Week 14) This week is left free for independent study.
Exam Period Any Exam or Quiz worth more than 30% of the final assessment will be scheduled in this two week period.
Assessment Due: Final Exam

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 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Graduate Certificate in Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Graduate Diploma in Computing 2015, 2016
Graduate Diploma in Information Technology 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Graduate Diploma in Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of Information Technology 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of Information Technology Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023
Master of IT/Master of IT Management 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

Course Goals

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

Attribute Practiced Assessed
Design (Level 3) Yes 19%
Engineering/IT Specialisation (Level 3) Yes 52.9%
Maths/Science Methods and Tools (Level 3) Yes 9.1%
Information Seeking (Level 3) Yes 6.9%
Communication (Level 3) Yes 10.3%
Professional Conduct (Level 3) No 0%
Project and Team Skills (Level 3) Yes 1.8%

These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 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.