A Picture Is Worth a Thousand Words
— Value of Visualization
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.
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.
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.
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!
|Ph.D Computer Science and Engineering, The Chinese University of Hong Kong||2011|
|M.Sc Computer and Information Science, University of Macau||2007|
|B.Eng. Computer Science and Technology, Huazhong University of Science and Technology||2004|
|B.A(Dual Degree) English||2004|
|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 Macau||2007|
|Research Assistant: The Chinese University of Hong Kong||2007-2009|
Lecture 01 (PDF) Introduction
Lecture 02 (PDF) From Graphics to Visualization
Lecture 03 (PDF) Data Representation
Lecture 04 (PPTX) Chapter 4 Visualization Pipeline
Lecture 05 (PPT) Chapter 5 Contouring
Lecture 05 (PPTX) Chapter 5 Color Mapping
Lecture 06 (PPTX) Chapter 6 Vector Color Coding
Lecture 07 (PPT) Chapter 5 Scalar Visualization
Lecture 08 (PPT) Chapter 5 Vector Visualization
Lecture 09 (PPT) Image Visualization
Lecture 10 (PPT) Chapter 10 Volume Visualization
Lecture 11 (PPT) Chapter 11 Information Visualization
Lecture 12 (PPT) Introduction and Basic Ray Tracing
Lecture 13 (PPT) Lighting and Reflection
Lecture 14 (PPT) Global Illumination
Due date: November 23rd, 2018
Final Report Template: (template)
Due date: January 11th, 2019
Send the electronic copy to firstname.lastname@example.org (including your name and student ID)
List of Proposed Final Projects (PDF)
If you have any problem, please contact us:
Sheng Bin (Email: email@example.com)
Anum Masood (Email: firstname.lastname@example.org)
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
Bonus:     5 points (for Research paper submission in Journal/Conference) on your final scores.
The template for Final Report is available here