ECE 595E 
Visualization Techniques

School of Electrical and Computer Engineering 
Purdue University

Fall 2008

Time: MWF 11:30-12:20pm   EE 226

Instructor:

Dr. David S. Ebert , ebertd at purdue dot edu, MSEE 274, Phone: (765)494-9064

Office Hour: MW 12:20- 1:00

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Description:

This course will cover topics in visualization: visual analytics, scientific visualization, medical visualization, and information visualization. The format for the course will be group discussions of papers, some lectures by the instructor, and some student presentations of papers. The grading will be based on participation in class, critical assignments, and class projects. Class projects may be done individually or in groups. Projects have the potential of leading to work that forms the basis of an Undergraduate research projects, Master's thesis, or Ph.D. research topic. A partial list of topics includes the following:

  • Visual analytics
  • Medical Visualization Techniques
  • Information Visualization Techniques
  • Flow Visualization Techniques
  • Visualization on mobile devices
  • Real-time Visualization Techniques
  • Non-Photorealistic Visualization
  • Terabyte Visualization
  • Scalar Visualization Techniques
  • Volume Visualization Techniques
  • Perception and Visualization
  • Visualization Design

General Course Schedule

  • Week 1 : Organization and Introduction to visualization
  • Week 2 : Overview of current trends and issues in visualization
  • Week 3 : Introduction to linking analysis and visualization - visual analytics
  • Week 4 : Challenge problem areas, usability and mobility
  • Week 5 : Basics of Graphics Review
  • Week 6 : Scalar Visualization
  • Week 7 : Information Visualization
  • Week 8 : Intro to Volume Visualization
  • Week 9 : Volume Visualization
  • Week 10 : Volume Visualization
  • Week 11 : Perception
  • Week 12 : Flow Visualization
  • Week 13 : Visualization Design, Geospatial Visualization
  • Week 14 : Medical Visualization
  • Week 15 : Illustrative Visualization
  • Week 16 : Project Presentations

Tentative Detailed Schedule

Readings: Students will read and discuss seminal and current technical research papers. A list of readings (in progress and subject to frequent update) is available here. For off campus access to restricted library resources (such as the ACM digital library), use the Libraries Proxy Service.

Prerequisites: EE 264, EE368, EE369 or permission of instructor

Textbook: There is no required textbook for this class.

The following books may also be useful as references.

  • The Visualization Handbook, by Charles Hansen and Christopher Johnson, Academic Press, 2005
  • Illuminating the Path: The R&D Agenda for Visual Analytics, Editors: James J. Thomas and Kristin A. Cook
  • The Visualization Toolkit: An Object-Oriented Approach to 3D Graphics, by William Schroeder, Ken Martin, Bill Lorensen, 2nd Edition, 1997, (ISBN 0-13-954694-4).
  • Readings in Information Visualization using Vision to Think by Stuart K. Card, Jock D. Mackinlay, and Ben Shneiderman, Morgan Kaufmann
  • Information Visualization, Robert Spence, Addison-Wesley

Course Outcomes

A student who successfully fulfills the course requirements will have demonstrated:

  • an understanding of the design issues for creating effective visualizations (1,4, b, c, j, k)
  • an ability to apply visualization techniques to an actual visualization problem and associated dataset. (1,3,4, a, c,e, k)
  • an ability to read, evaluate, and present technical papers (3,6, a, g)
  • an understanding of scalar, volume, and surface-based visualization techniques (1,3,4, a )
  • an understanding of the issues and techniques for applying visualization to one of the following visualization problems: medical, flow, scientific, and information (abstract data) (1,3, 7,a, b, j)
  • an ability to design an effective visualization solution for a problem (2,3,4, a, c, e, k)
  • an ability to present their design and resulting system (6, g)

Assessment Methods

The course outcomes will be assessed through student demonstration of a completed visualization project, submission of working program(s), oral and written presentation of results (literature survey, alpha release report, beta release report, regular meetings of project teams with the instructor, and the final project report). The overall knowledge acquisition of visualization techniques will be assessed by student oral presentations of papers, through the completion of a literature review, and through several initial project assignments.

Grades:
Grades will be assigned on the basis of paper reading and evaluation (25%), initial visualization project (15%), discussions/presentations of technical papers and class participation(15%), and class projects (45%). Phases may be turned in up to one week after the due date with a 30% grade penalty. Phases will not be accepted more than a week late. Plus/minus grading will be used in this class.

Teaching Assistants:

Ross Maciejewski rmacieje at purdue dot edu, POTR 134, Phone: (765)494-5945
Office Hour: T 3:00 - 4:00

FOR MORE INFORMATION

Contact David Ebert, ebertd at purdue dot edu