Course Homepage-Computer Graphics

General Information:

Course: CS 4/5/6/79995, Fall 2011

Time: Tuesday, Thursday 2:15am-3:30pm

Room: MSB 121

Instructor:

Ye Zhao, Assistant Professor

Office: MSB 220

Email: zhao@cs.kent.edu

Office Hours: Tuesday, Thursday 1:15 pm - 2:15 pm or by appointment

Syllabus

PDF version

Homework2 Design Contest Awards:

Graduate

First Tier: Harsha Vardhan Bathula, Peter Correia, Jeremy Miller, Sean Reber, David Sheets

Second Tier: Aditya Chintala, Shruti Sanjay Jadhav, Poornakumar Rasiraju, Yingyu Wu, Robert Gilliland

Undergraduate

First Tier: Joseph Carioti, Jason Cleveland

Second Tier: Rafia Qureshi, Nathaniel Snyder

Course Notes, Homework and Projects

Technical Paper Presentation

Team Projects

Homework2 Presentations

Goal:

Information visualization is the science that unveils the underlying structure of data sets using visual representations that utilize the powerful processing capabilities of the human visual perceptual system. In this class, we will study algorithms and systems for visually exploring, understanding, and analyzing large, complex data sets. Information visualization focuses on abstract data such as symbolic, tabular, networked, hierarchical, or textual information sources. The objectives of the course are to learn the principles involved in information visualization and a variety of existing techniques and systems. The students will also gain backgrounds and skills that will aid the design of new, innovative visualizations in realistic applications.

Please see at the bottom of this page for a few examples of the fascinating visualizations in a variety of applications.

Topics:

Topics of this course include

1) multidimensional visualization, tree visualization, graph visualization, and time series data visualization techniques;

2) visual perception, cognitive issues, evaluation, as well as other theory and design principles behind information visualization;

3) basic interaction techniques such as selection and distortion; evaluation;

4) examples of information visualization applications and systems.

Prerequisite:

None. Very basic math contents will be involved.

Text:

There is no required textbook for this course. We will make class notes and papers available instead.

A list of books is recommended:

Interactive Data Visualization by M. Ward, G. Grinstein, and D. Keim, A.K. Peters 2010

Now You See It by Stephen Few, Analytics Press 2009.

Information Visualization: Perception for Design. by Colin Ware, Morgan-Kaufmann.

Envisioning Information by Edward Tufte, Graphics Press 1990

Assessment:

No paper examinations for the course. Grading will be based on class participation, short homework, reading assignments, and projects (maybe in groups)

Resources:

1. Dr. John Stasko's Information Visualization course materials

http://www.cc.gatech.edu/~stasko/7450/09/

He listed many other related course resources:

http://www.cc.gatech.edu/~stasko/7450/09/courses.html

2. Dr. Jing Yang’s Information Visualization course

http://coitweb.uncc.edu/~jyang13/infovis2010.html

3. XmdvTool homepage

http://davis.wpi.edu/~xmdv/

4. HCIL Homepage

http://www.cs.umd.edu/hcil/

5. InnoVis Homepage