1. Instructor: Dr. Wen-Hung Liao 2/21/2017

2. Outline Course Instructor Social Multimedia Computing: Why and How
Multimedia Basics
Graphics and Image Data Representation
Color in Image and Video
Fundamental Concepts in Video
Basic of Digital Audio
Social Multimedia Computing
Readings

3. About the Instructor Dr. Wen-Hung Liao whliao@gmail.com
Dept. of Computer Science, National Chengchi University
Course website:
Textbook (for this part): Fundamentals of Multimedia, 2nd edition, (local copy)

4. Quick Survey Prior background in: Digital signal processing
Digital image processing
Computer vision
Multimedia
Machine learning, Deep learning
Data mining
Social network

5. Applications and Tools (1/3)

6. Applications and Tools (2/3)
Multimedia Grand Challenges 2016
Master’s thesis under my supervision
Identifying User Profile Using Facebook Photos
Color Analysis of Instagram Photos and Its Application

7. Applications and Tools (3/3)
Object recognition:
Content-Based Image Retrieval (CBIR)
Text Parsing
Stanford CoreNLP:
JIEBA
Academia Sinica:
Word2vec

8. Multimedia Basics Chapter 3 : Graphics and Image Data Representation
Chapter 4: Color in Image and Video
Chapter 5: Fundamental Concepts in Video
Chapter 6: Basic of Digital Audio

9. Chapter 3 3.1 Graphics/Image Data Types 3.2 Popular File Formats
1-bit images
8-bit gray-level images
Image data types
24-bit color images
Higher bit-depth images
8-bit color images
Color lookup tables (LUTs)
3.2 Popular File Formats

10. Multimedia Viewer XnView http://www.xnview.com/en/xnview/
Perception of gray scale images

11. More on Dithering
Median Cut Algorithm
Color Quantization

12. Higher bit-depth images
Medical imaging (10-bit gray level)
Multispectral imaging

13. EXIF Not supported in JPEG 2000, PNG and GIF.
Q1: What information can be obtained by analyzing the EXIF?
Q2: Can you read exif data from pictures on facebook or instagram?

14. PTM Format
Polynomial texture mapping: a technique for storing a representation of a camera scene that contains information about a set of images taken under a set of lights that each have the same spectrum, but with each placed at a different direction from the scene.

15. PTM Example

16. Chapter 4 4.1 Color Science 4.2 Color Models in Images
4.3 Color Models in Video

17. Color Space Conversions
OpenCV function: cvtColor

18. Readings Chapter 3, 4 of the textbook (required)
Social multimedia computing. (required)
User-centric social multimedia computing. (optional)