ECE 595-003: Visualization Techniques

Announcements

December 6, 2014: The final course project presentations schedule is as follows: Mon (12/8): CY, EK, JZ & JXT; Wed (12/10): GW, YHH, MC, MK, SD; Fri (12/12): JHZ & HX, SW, SJ, CG, YC

October 14, 2014: The grades for your design document have been posted on Blackboard. Looking forward to the alpha release!

October 3, 2014: Here’s the link to the Lytro camera that Dr. Ebert mentioned in class on Monday: Link.  Check out the images from Lytro here.

September 19, 2014: The VisualRepresentations assignment has been graded.  You should have received feedback on Blackboard.

August 29, 2014: Here’s the link to the red vs. blue website that Dr. Ebert mentioned in class on Wednesday: Link.

August 27, 2014: The VisualRepresentations assignment has been released (Link).  Due date: Friday, September 5 (in class).

Introduction

Visualization is the graphical representation of data to aid understanding, and is the key to analyzing massive amounts of data for fields such as science, engineering, medicine, and the humanities. In this course, intended for graduate and advanced undergraduate students, you will learn how to apply these exciting techniques to practical problems and work on state-of-the-art research projects that could lead to a publication in one of the prestigious IEEE VisWeek conferences!

This course will serve as an introduction to the science and technology of visualization. The course contents will include both theoretical foundations of this interdisciplinary science as well as practical applications of integrated visualization techniques on real-world problems.

Overview

This course will cover topics in visualization such as 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 project, Master's thesis, or Ph.D. research topic.

Instructors

Dr. David Ebert

·         Office: POTR 228

·         Office hours: Fri 1:30pm – 2:30pm, or by appointment

·         Email: ebertd@purdue.edu

 

Dr. Abish Malik

·         Office: POTR127B

·         Office hours: Tue 1pm-2pm, or by appointment

·         Email: amalik@purdue.edu

Readings

There is no official textbook for this course. Students will read and discuss seminal and current technical research papers. A list of readings (in progress and subject to frequent update) is available on the course website.

The following books may be useful as references.

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.

Academic Integrity

Students must conform to Purdue's policy on academic integrity. More specifically, Purdue prohibits "dishonesty in connection with any University activity. Cheating, plagiarism, or knowingly furnishing false information to the University are examples of dishonesty." [University Regulations, Part 5, Section III, B, 2, a]

Here is a non-exhaustive list of examples of dishonest behavior:

In particular, this includes copying text from research papers you are summarizing, unless you properly quote and cite the text you copied. If you copy text from existing papers and try to pass this off as your own, you are committing severe plagiarism and you will have to face the consequences.

Note that class projects may involve several students, in which case collaboration and sharing between project members naturally is allowed.

For more information, see Purdue’s online brochure on academic integrity:http://www.purdue.edu/odos/osrr/academicintegritybrochure.php

Cheating or otherwise abusing academic integrity (at the discretion of the instructors) will at the minimum result in a zero grade for the assignment or exam, and will likely result in a failing grade for the whole course. The instructors will also initiate disciplinary actions with Purdue.

Campus Emergencies

In the event of a major campus emergency, course requirements, deadlines and grading percentages are subject to changes that may be necessitated by a revised semester calendar or other circumstances. In such an event, information will be provided through Blackboard Learn and through the course website.

 

Detailed Schedule (Tentative)

Week 1 (Aug. 25-31):
                Monday – Course Organization

                Wednesday – Assignment

                Friday – Introduction to Visualization

Week 2 (Sept. 1-7):

                Monday – Labor Day holiday – No Class

                Wednesday – Open Research Questions in Visualization

                Friday – Color, Perception, Cognition

                                VisualRepresentations assignment due

Week 3 (Sept. 8-14):

                Monday – Discussion of the VisualRepresentations assignment

                Wednesday – Graphics for Visualization

                Friday – Presentations (Course Project: Proposals)

Week 4 (Sept. 15-21):

                Monday – Data Models

                Wednesday – Multidimensional Visualization

                Friday – Presentations (Paper presentations)

Week 5 (Sept. 22-28):

                Monday – Time

                Wednesday – Spatiotemporal Visualization

                Friday – Presentations (Paper presentations)

                Sunday – Course Project: Literature review due

Week 6 (Sept. 29-Oct. 5):

                Monday – 3D Visualization I

                Wednesday – 3D Visualization II

                Friday – Presentations (Paper presentations)

                Sunday – Course Project: Design document due

Week 7 (Oct. 6-12):

                Monday – Text

                Wednesday – Guest Lecture: Prof. Xavier Tricoche (Flow Visualization)

                Friday – Presentations (Paper presentations)

Week 8 (Oct. 13-19):

                Monday – Fall Break – No Class

                Wednesday – Guest Lecture: Prof. Ji Soo Yi (Interaction)

                Friday – Graphs and Trees

                Sunday – Course Project: Alpha release due

Week 9 (Oct. 20-26):

                Monday –Animation

                Wednesday – Collaboration

                Friday – Presentations (Paper presentations)

Week 10 (Oct. 27–Nov. 2):

                Monday – Visual Analytics

                Wednesday – Visual Analytics II

                Friday – Presentations (Paper presentations)

Week 11 (Nov. 3-9):

                Monday – Visualization for Mobile Devices, Large Displays, and Ubiquitous Computing / Visualization on the Web / Visualization Design and Principles

                Wednesday – Space

                Friday – Presentations (Paper presentations)

Week 12 (Nov. 10-16):

                Monday – VisWeek

                Wednesday – VisWeek

                Friday – Presentations (Paper presentations)

                Sunday – Course Project: Beta release due

Week 13 (Nov. 17-23):

                Monday – Guest Lecture: Prof. Alexander Quinn (HCI)

                Wednesday – Guest Lecture: Prof. Alexander Quinn (Perception)

                Friday – Presentations (Paper presentations)

                Sunday – Course Project: Paper draft due (optional)

Week 14 (Nov. 24-30):

                Monday – Production, Presentation, Dissemination

                Wednesday – Thanksgiving Break – No Class

                Friday – Thanksgiving Break – No Class

Sunday – Course Project: Final paper due

Week 15 (Dec. 1-7):

                Monday – Conducting Research in Visualization and Visual Analytics

                Wednesday – Presentations (Paper presentations)

                Friday – Presentations (Paper presentations)

                                Course Project: Final Release

                                Paper Reviews due

Week 16 (Dec. 8-12):

                Monday – Project Presentations I

                Wednesday – Project Presentations II

                Friday – Project Presentations III


 

Grades

Grades will be assigned on the following grounds:

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.

Class Project Grading:

 

Activity

Deadline

Grade %

Project Proposal

September 14

5

Literature Review

September 28

5

Design

October 5

5

Alpha Release

October 19

5

Beta Release

November 16

5

Paper Draft (Optional)

November 23

--

Paper

November 30

10

Final Release

December 7

10

Reviews

December 7

5

Presentation

Mon/Wed/Fri

5

Total Grades for Project

 

55

 

Course Project

Details on the course project are available here.

Paper Summaries

Details on the paper summaries are available here.

 VisualRepresentations Assignment

Details on the VisualRepresentations assignment are available here.