Type of Credit: Partially Required
Credit(s)
Number of Students
Outline:
1. Introduction to Multimedia
1.1. What is Multimedia?
1.2. Overview of Multimedia Applications
1.3. Multimedia Research Resources
2. Multimedia Basics
2.1. Graphics and Image Data Representations
2.2. Color in Image and Video
2.3. Fundamental Concepts in Video
2.4. Basics of Digital Audio
3. Multimedia Processing & Coding
3.1. Video coding fundamentals
3.2. Lossless Compression & Lossy Compression
3.3. Transform Coding
3.4. Motion Compensated Predictive Coding
4. Multimedia Coding Standards
4.1. JPEG, JPEG-2000
4.2. H.261, H.263, MPEG-1, MPEG-2, MPEG-4, and H.264
5. Social Network Basics
5.1. An Introduction to Social Networks
5.2. Properties and Models of Social Networks
5.3. Centrality Analysis and Community Detection
5.4. Information Diffusion in Social Networks
6. Social Multimedia Analytics
6.1. Sentiment, Opinion, Locations, and Multimedia
6.2. Search and Recommendation in Social Media
7. Machine Learning in Social Multimedia Analytics
7.1. Unsupervised Learning
7.2. Discriminative Models
7.3. Generative Graphical Models
8. Advanced Multimedia Processing
8.1. Image Manipulation Techniques
8.2. Interactive Multimedia Editing
能力項目說明
Dr. Jun-Cheng Chen (Chair)
Dr. Chia-Wen Lin
Dr. Wen-Hung Liao
Dr. Yan-Tsung Peng
Dr. Li Su
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
|
Week |
Date |
Topics/Brief Description |
|
1 |
2024/09/11 |
Introduction to Multimedia |
|
2 |
2024/09/18 |
Multimedia Basics (I) |
|
3 |
2024/09/25 |
Multimedia Basics (II) |
|
4 |
2024/10/02 |
Audio Analysis in Multimedia (I) |
|
5 |
2024/10/09 |
Audio Analysis in Multimedia (II) |
|
6 |
2024/10/16 |
Fundamental of Deep Learning (I) |
|
7 |
2024/10/30 |
Fundamental of Deep Learning (II) Final-Project Proposal Explanation (Milestone I) |
|
8 |
2024/11/06 |
Visual Content Processing & Coding (I) |
|
9 |
2024/11/13 |
Visual Content Processing & Coding (II) |
|
10 |
2024/11/20 |
Image/Video Coding Standards |
|
11 |
2024/11/27 |
Final-Project Proposal Presentation (Milestone II) |
|
12 |
2024/12/04 |
Midterm Exam |
|
13 |
2024/12/11 |
Deep Learning for Image Processing Applications (I) |
|
14 |
2024/12/18 |
Deep Learning for Image Processing Applications (II) |
|
15 |
2024/12/25 |
Deep Learning for Image Processing Applications (III) |
|
16 |
2024/05/31 |
Social Multimedia and Related Applications Final-Project Clinic (Milestone III) |
|
17 |
2025/01/01 |
HOLIDAY |
|
18 |
2025/01/08 |
Final |
Grades:
Class Participation (10%)
Homework Assignments: (20%)
Midterm Exam (30%)
Final Project (40%)
Proposal: 10%
Demo: 20%
Report: 10%
Textbook/Reference:
Ze-Nian Li, Mark S. Drew, and Jiangchuan Liu, Fundamentals of Multimedia, 2nd edition, Springer, 2014.
Gonzalez and Woods, Digital Image Processing, 3rd edition, Prentice Hall, 2008.
Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2007.
Richard Szeliski, Computer Vision: Algorithms and Applications, Springer, 2010.
Richard J. Radke, Computer Vision for Visual Effects, Cambridge University Press, 2012.
S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications, Cambridge University Press, 1994.
R. A. Hanneman and M. Riddle, Introduction to Social Network Methods, University of California, 2005.
http://faculty.ucr.edu/~hanneman/nettext/Introduction_to_Social_Network_Methods.pdf
R. Zafarani, M. A. Abbasi, and H. Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014.
Charu C. Aggarwal, Social Network Data Analytics, Springer, 2011.
W. Chen, L. V.S. Lakshmanan, and C. Castillo, Information and Influence Propagation in Social Networks, Morgan & Claypool Publishers, 2013.
Selected research papers.