Course Description

A Picture Is Worth a Thousand Words

A Picture Is Worth a Thousand Words

— Value of Visualization

Brief Description

Two main parts of the course include "Computer Animation" and "Data Visualization"

Animation is a captivating and effective form of expression which not only engages viewers but also makes the difficult concept easier to understand. Nowadays animation industry creates movies, special effects, and games with spectacular visual detail and quality. Computer animation section emphasizes mainly on the scientific characteristics for 3D computer animation for applications such as games and virtual environments. Visualization is a cognitive process using the powerful information processing and analytical functions of the human vision system. It has always been a major aspect in scientific development and now, with the support of computer graphics, it encompasses our visualization system from sub-atomic to interstellar scopes and permits geometric illustration and simulations of any multidimensional dataset. The essential goal is to obtain novel understanding rather than breeding pictures. This part is very concrete and methods will be demonstrated through applications in the scientific, engineering and medical fields. The progressively significant area of information visualization and visual data-mining will also be covered.

Indicative Syllabus

The course will focus on the variability of methods and procedures used to envision data complex concepts with the help of Computer Graphics. It mainly researches how to transform the scientific data, including the computation and measurement data, the images transmitted from satellites, and the images from CT and MRI devices, into the messages which can be viewed intuitively and is helpful to understand. The techniques of Computer Animation and Data Visualization have wide-spread applications in molecular modeling, medicine imaging, geoscience, space exploration, computational fluid dynamics, finite element analysis, etc. The lectures provide the theoretical framework necessary to work with information visualization. These cover methods for interactive visualization of large complex data sets. In this course, we will study techniques and algorithms for creating effective visualizations based on principles of graphic design, visual art, perceptual psychology, and cognitive science. Students are required to learn the research background of scientific data visualization and to skill in the basic concepts and core algorithms in visualization. The main contents include the algorithms of contour extraction in 2D scalar fields, surface reconstruction between planar cross sections, isosurface generation, and rendering, and volume rendering. The students will propose novel techniques and explore new methods for computer animation and data visualization in semester-long research projects. This course is recommended for students with general interest in computer animations, computer animation as well as for students who are interested in new applications of data-visualization, computer graphics, data-mining, machine learning and scientific computing.

Course Aims

After completing the course, the student should be able to:

Course Credit: 3

P.S.: This course can provide a fundamental background for your research work, So take this course for the intellectual and academic interest.

Course Schedule

  1. Time: Friday 18:00PM - 20:00PM
  2. Duration: Week 1 to Week 16
  3. Classroom: Room 309, Rui-Qiu Chen Building (陈瑞球楼309)
  4. Office Hours: Friday 14:00 pm to 15:00 pm

Recommended Textbooks

  1. 1. The Visual Display of Quantitative Information (2nd Edition). E. Tufte. Graphics Press, 2001.
  2. 2. 《科学计算可视化-算法与系统》. 石教英,蔡文立. 科学出版社。1996年9月.
  3. 3. Data Visualization–Principles & Practice, Alexandru C. Telea, A K Peters, 2008
  4. 4. Handbook of Data Visualization


      • Instructor: Dr. SHENG Bin (盛斌)
      • Associate Professor, Ph.D.
      • Email: shengbin AT
      • Office: SEIEE #3-539 Tel: (021)3420-7642
      • Lab: Visual Media and Data Management

      Research Interest

    • 1. Image-based Modeling and Rendering, Animation, Image Processing, Natural Phenomenon Simulation/Non-photorealistic Rendering and GPU Processing.

    • 2. Virtual Reality, Augmented Reality

    • 3. Data Visualization and Biomedical Imaging

    • Looking for highly motivated, talented graduate students (both M.Sc and PhD students) for cutting-edge research in graphics, virtual reality, multimedia, and GPU Processing!

      Education Background

      Ph.D Computer Science and Engineering, The Chinese University of Hong Kong2011
      M.Sc Computer and Information Science, University of Macau2007
      B.Eng. Computer Science and Technology, Huazhong University of Science and Technology2004
      B.A(Dual Degree) English2004

      Working Experiences

      Associate Director: Lab For Digital Media and Data Reconstruction (SJTU) 2011-Present
      Technical Consultant: Hong Kong Applied Science and Technology Research Institute (ASTRI)2012-Present
      Research Assistant: University of Macau2007
      Research Assistant: The Chinese University of Hong Kong2007-2009

      Teaching Assignments

      1. Scientific Data Visualization (
      2. Computer Animation Modeling and Rendering
      3. Computer Animation Design and Rendering
      4. Practice on Computer Animation

      For further details click here.

Course Lecture Videos

[1] Introduction to Deferred Shading
[2] More about Deferred Shading
[3] Realism and Media

Course Notes

  1. Lecture 01 (PDF) Introduction

  2. Lecture 02 (PDF) From Graphics to Visualization

  3. Lecture 03 (PDF) Data Representation

  4. Lecture 04 (PPTX) Chapter 4 Visualization Pipeline

  5. Lecture 05 (PPT) Chapter 5 Contouring

  6. Lecture 05 (PPTX) Chapter 5 Color Mapping

  7. Lecture 06 (PPTX) Chapter 6 Vector Color Coding

  8. Lecture 07 (PPT) Chapter 5 Scalar Visualization

  9. Lecture 08 (PPT) Chapter 5 Vector Visualization

  10. Lecture 09 (PPT) Image Visualization

  11. Lecture 10 (PPT) Chapter 10 Volume Visualization

  12. Lecture 11 (PPT) Chapter 11 Information Visualization

  13. Lecture 12 (PPT) Introduction and Basic Ray Tracing

  14. Lecture 13 (PPT) Lighting and Reflection

  15. Lecture 14 (PPT) Global Illumination

Course Evaluation

    • Final Project Presentation: 40%
    • Final Project Report and Code: 60%
    • Project Proposal: 20 marks
    • Project Presentation: 25 marks (15th Week )
    • Project Final Report: 25 marks
    • Project Implementation (source code and dataset): 30 marks
    • Project Proposal:

    • Due date: November 23rd, 2018

    • Final Report Template: (template)

    • Due date: January 11th, 2019

      Submission way:

      Send the electronic copy to (including your name and student ID)

Final Project

  1. List of Proposed Final Projects (PDF)

    Project Proposal Score:    

    (Click here to download the Project Proposal Scores.)

Contact us

    If you have any problem, please contact us:

    Sheng Bin (Email:

    Teaching Assistant:
    Anum Masood (Email:

    Students can select a project of their own choice too but the project should be relevent to the course.

    Students can do project individually or in a group of two students

    Deadline to select the course project is 21st October 2018

    Students are requested to send the details of group members including names and student ID and selected project title on the following email address:

    Bonus:     5 points (for Research paper submission in Journal/Conference) on your final scores. The template for Final Report is available here