DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING

NORTHEASTERN UNIVERSITY

EECE 5642 Data Visualization

Spring 2021

Instructor: This class will be taught by  Yu Yin

Office: 427 Richards Hall

Email: yin.yu1@northeastern.edu

Electronic communication: We will use Canvas 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 Canvas has for you is one you check regularly.

 

Prereq. Basic programming skills, knowledge of fundamental data structures and algorithms

Teaching Assistant: Lichen Wang, SMILE Lab, Room 427, Richards Hall, Email: wang.lich@northeastern.edu

Class and Office Hours:

Class Hours : Monday and Thursday 11:45 am - 01:25 pm via Zoom

Office Hours: TBA (Conducted via Zoom)

 

Important Note:

This course will be delivered using the Hybrid NUflex learning modality and I will be teaching remotely. I will join you virtually in the class at the scheduled class time using [video platform, usually Zoom or Teams] with some students in the classroom and others joining remotely. You will be able to ask questions, discuss, and interact with me and other students in real time. Remember that on your scheduled days in the classroom, you will need to practice healthy distancing and wear a face mask or face covering. I will also be available for virtual office hours on the days/times in the syllabus.

 

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 18 & 21

No class (Martin Luther King Jr.'s Birthday)

Introduction

 

2

Jan 25 & 28

Data Representation

Image Model and Human Vision System

 

3

Feb 01 & 04

Visual Cognition

Visual Perception

HW 1

 

4

Feb 08 & 11

Visualization Design

Trees and Networks & HW1 Recitation [TA]

 

5

Feb 15 & 18

No class (Presidents' Day)

Color and Visualization Tools

HW 2

 

6

Feb 22 & 25

Dimensionality Reduction

Table and Graph

7

Mar 01 & 04

Mid-term Exam (Take-home exam, no class)

Paper Discussion

Mid-term

8

Mar 08 & 11

Paper Discussion

Paper Discussion

HW 3

9

Mar 15 & 18

Paper Discussion

Maps, Mid-term Exam Recitation [TA]

 

10

Mar 22 & 25

Interactive Visualization [Guest]

Proposal Presentations

 

11

Mar 29 & Apr 01

Human and Face Visualization [Guest]

Image-based Rendering and Beyond [Guest]

 

12

Apr 05 & 08

HW3 Recitation [TA]

No class (Prelim Preparation)

 

13

Apr 12 & 15

Project Presentations

Project Presentations

 

14

Apr 19 & 22

No class (Patriots' Day)

Project Presentations

 

15

Apr 29

 

Final Report Due at 5pm

Final

 

* Guest lecturers will be invited to present some topics if funding is available for honoraria or expenses.

 


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 Canvas on time, 5pm on Apr 29.

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.

 

This syllabus is updated on Jan 15, 2021