DEPARTMENT OF ELECTRICAL AND
COMPUTER ENGINEERING
NORTHEASTERN UNIVERSITY
EECE 5642 Data
Visualization
Spring 2020
Instructor: This class will be taught by Mr. Yulun Zhang
Office: 427 Richards Hall
Email: zhang.yulu@husky.neu.edu
Electronic communication: We will use Blackboard for posting assignments, notes,
any on-line discussions, and other forms of electronic communication. It will
be assumed that you check your email regularly, and it is your responsibility
to make sure that the instructor has a good email address for you. In
particular you should make sure that the email address that Blackboard has for
you is one you check regularly---you can change it if you wish on Blackboard.
Prereq. Basic programming skills, knowledge of fundamental data structures and algorithms
Teaching Assistant: Ms. Huixian Zhang, SMILE Lab, Room
427, Richards Hall, Email: zhang.hu@husky.neu.edu
Class
and Office Hours:
Class Hours : Monday and Thursday 11:45 am - 01:25 pm in West Village H 110
Office Hours: Tuesday 09:00 am - 11:00 am in Ricards Hall 427
Textbook
Class lecture slides will be
provided by the instructor, either printout or electronic file. Students will
be asked to find more self-learning content from Internet resources.
Recommended textbooks are:
Catalog Course Description: Introduction to relevant topics and concepts in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concept, animation techniques, pattern analysis, and computational methods. Tools and techniques for practical visualization. Elements of related fields including computer graphics, human perception, computer vision, imaging science, multimedia, human‐computer interaction, computational science, and information theory. Covers examples from a variety of scientific, medical, interactive multimedia, and artistic applications. Hands‐on exercises and projects.
Grading
Students will be graded on class participation, three assignments, a mid-term examination, a mid-term project and a final project and presentation. The final grade will be composed as follows:
Class Participation.................. 10%
Homework............................. 30%
Mid-Term Exam..................... 20%
Final Project........................... 40%
Course Topics and Schedules
|
Week |
Date |
Monday
|
Thursday
|
HW |
Exam |
|
1 |
Jan 06 & 09
|
Introduction
|
Data Representation
|
|
|
|
2 |
Jan 13 & 16
|
Image
Model and Human Vision System
|
Visual Cognition |
HW 1 |
|
|
3 |
Jan 20 & 23
|
No class (Martin Luther King Jr.'s Birthday)
|
Visual Perception
|
|
|
|
4 |
Jan 27 & 30
|
Visualization
Design
|
Trees and Networks & HW1 Recitation [TA]
|
|
|
|
5 |
Feb 03 & 06
|
Color and Visualization
Tools
|
Dimensionality
Reduction
|
HW 2 |
|
|
6 |
Feb 10 & 13
|
Table
and Graph
|
Mid-term Exam (Take-home exam, no class)
|
Mid-term
|
|
|
7 |
Feb 17 & 20
|
No class (Presidents' Day)
|
Paper Discussion
|
|
|
|
8 |
Feb 24 & 27
|
Paper Discussion
|
Paper Discussion
|
HW 3 |
|
|
9 |
Mar 09 & 12
|
Paper Discussion
|
Maps, Mid-term Exam Recitation [TA]
|
|
|
|
10 |
Mar 16 & 19
|
Interactive Visualization [Guest] |
Proposal
Presentations
|
|
|
|
11 |
Mar 23 & 26
|
Human and Face
Visualization [Guest] |
Image-based Rendering and
Beyond [Guest]
|
|
|
|
12 |
Mar 30 & Apr 02
|
HW3 Recitation [TA] |
Geographic Visualization [Guest] |
|
|
|
13 |
Apr 06 & 09
|
No class (Prelim Preparation)
|
Project
Presentations
|
|
|
|
14 |
Apr 13 & 16
|
Project Presentations
|
Project
Presentations
|
|
|
|
15 |
Apr 20 & 23
|
No class (Patriots' Day)
|
Final Report Due at 5pm
|
Final |
* Guest lecturers will be invited to
present some topics if funding is available for honoraria or expenses.
* Courtesy of Prof. Hanspeter
Pfister, Harvard University.
Final Project
The final project has two options: visualization demo design or software tool design. The basic idea of the two directions is the same which is to collect some scientific data and visualize them. The demo design mainly focuses on the visual animations, 2D/3D graphics, video making, and computer vision based visualization techniques. The tool design is mainly to design and implement a visualization tool that can analyze the data with any kind of visualization concepts or formats, summarize some useful results/conclusions, answer questions, and provide suggestions or comments. The data should be real data, which can be either collected by individual or borrowed from somewhere (with permission and acknowledgement). Students can use any API or programming language they like. Students can work on the project by themselves or team up with other students in the class. The team members cannot be more than two.
To grade the final project, three aspects will be considered. 1) proposal presentation (20%); 2) final project presentation (30%); 3) final project report and software package (50%). Late submission without instructor permission may not be considered. Typically, we do not anticipate that the grades for each team member will be different. However, we reserve the right to assign different grades to each team member if the efforts or contributions they make are apparently different and unbalanced. Bonus points may be earned if the project shows significant novelty and large potentials for real-world applications. Those projects may get our guidance for further paper publications.
Proposals
and Reports
Please consider following
contents when you prepare for your proposals and final reports:
Project
Presentations
PPT or PDF slides and demos can be used for final project
presentations.
Schedule: TBA
Submission
The presentation
slides, the final report and software package should be submitted to Blackboard
on time, 5pm on Apr 23.
Policy: If submitting latter than 5pm without permission, we will reduce the
score with a penalty of 20%. If submitting after midnight of today without
permission, we do not count it as a successful submission.