Professor |
Bill T. Luo
|
Teaching assistants |
Yichao Fu
Junming Wang
|
Syllabus |
This course presents fundamental concepts
and emerging technologies for multimedia computing. Students are expected to
learn how to develop various kinds of media communication, presentation, and
manipulation techniques. At the end of course, students should acquire
proper skill set to utilize, integrate and synchronize different information
and data from media sources for building specific multimedia applications. Topics include media data acquisition methods and techniques; nature of
perceptually encoded information; processing and manipulation of media data;
multimedia content organization and analysis; trending technologies for
future multimedia computing. |
Introduction by Professor |
Computing devices interacts with human based on three (out of five)
primary senses: Sight, Hearing and Touch. Multimedia computing deals
with multiple media data in relation to these senses to process and
convey information to and from human. The challenge for multimedia
computing systems is to integrate the different media information
streams into a coherent view. The use of multimedia data in
computing has grown even more rapid than imagined due to the boom in
Internet of Things (IoT), as well as the abundantly available
camera-equipped cell phones with the ability to share multimedia
contents in social networks. In this course, we present multimedia
as a fundamental and unique discipline that takes advantage of all
media available to solve problems. Graduate students can learn from
this course the fundamentals of multimedia computing, and get hold
of emerging technologies to prepare themselves to embrace the future
development of multimedia computing.
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Learning Outcomes |
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Pre-requisites |
Nil |
Compatibility |
Nil |
Topics covered |
|
Assessment |
|
Course materials |
Prescribed textbook:
- Multimedia Computing, by Gerald Friedland & Ramesh Jain, Cambridge University Press
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Session dates |
|
Add/drop |
1 September, 2022 - 15 September, 2022 |
Maximum class size |
150 |