CMSC 491/691: Computer Vision
Instructor: Tejas Gokhale (OH: Wednesday 2 PM - 3:30 PM or by appointment); ITE 214
Teaching Assistant: Aidin Shiri (OH: Monday and Thursday 2 PM - 3:45 PM); ITE 340
Time: Monday and Wednesday 4:00pm - 5:15pm
Location: Engineering 231
Course description
This course will offer a comprehensive introduction to the field of computer vision which has the broad goal of understanding visual signals (images and videos) for low/mid/high-level perceptual tasks. This course will introduce fundamental principles and concepts for developing computer vision systems such as image formation, acquisition, and processing, stereo and 3D vision, machine learning algorithms and neural networks for image understanding.
Prerequisites:
We will assume that you have a basic (but solid) expertise in linear algebra, geometry, probability, and Python programming.
Recommended classes at UMBC are: MATH 221 (Linear Algebra), STAT 355 or CMPE 320 (Probability and Statistics), MATH 151 (Calculus and Analytical Geometry).
If you are unfamiliar with linear algebra or calculus, you should consider taking both: without these tools, you are likely to struggle with the course. Although we will provide brief math refreshers of these necessary topics, CMSC 491/691 should not be your first introduction to these topics.
Homework 0 (an ungraded homework available on demand, that will NOT contribute to your grade) is meant to be a reflection of these prerequisites.
If you struggle with HW0, please get in touch with the instructor as soon as possible to discuss remedial options before the drop deadline (09/13).
We understand that some students may have had some prior exposure to signal/image/audio processing, computer graphics, machine learning, etc. However, none of these are pre-requisites -- the class is designed to be self-contained.
Reference Books
There are no required textbooks. The following books may be useful to accompany the lectures:
Schedule
Schedule is tentative and subject to change
|
| Topic |
Resources |
Announcements |
| 1 |
Introduction |
[slides] |
|
| 2 |
Image Formation and Acquisition |
[slides] Szeliski Ch 2 |
|
| 3 |
Image Filtering I |
[slides] Szeliski Ch 3 |
|
| 4 |
Image Filtering II |
[slides] Szeliski Ch 3 |
HW 1 released. Due 09/29 |
| 5 |
Image Features I |
[slides] |
|
Homework
- HW 1 has been released on Blackboard. Due on Sept 29, 2023 23:59 UMBC time.
Grading
- Homework Assignments: 40%
- Midterm Exam: 15%
- Scribing: 5%
- Project: 40%
Work hard, be attentive in class and participate in discussions, enjoy the homeworks, be creative in your projects, and seek help when needed!
Projects
The class has a mix of PhD, MS, and BS students. Projects will be judged on the basis of relative growth (from where you start to where you end).
- BS or MS (coursework) students: Pick one of the suggested topics. If you want to work on a cool idea of your own, come see Tejas and we can create a concrete structure and gameplan. I recommend working in groups of 4 students.
- PhD or MS (thesis) students: Consult with Tejas during Office Hours and discuss your existing research agenda. We will integrate the course project into that agenda if possible. Group sizes (or individual projects) will be decided on a case-by-case basis.
- Due dates:
- Project proposals (one per group, 2 page maximum):
- Project presentations:
- Project report (one per group, 8 page maximum, CVPR format):
-
Proposal: Clearly state the following:
- Problem you wish to tackle (and why)
- Proposed approach and methods
- Timeline
- What each student in the group will do.
- Expected Outcome and Worst-Case Outcome
- Detailed proposal, presentation, and report guidelines can be found here
Scribing
Please use this template for scribing.
For a quick tutorial on LaTeX, visit: this Overleaf Tutorial.
Schedule for scribing can be found here (read only).
If you want to request scribing for a particular lecture, please leave a comment on this spreadsheet or send an email to aidins1@umbc.edu .
To submit, email your notes as PDF, with subject: "[Scribing Submission] lecture-date" to gokhale@umbc.edu AND aidins1@umbc.edu .
Late Submissions
Each student will get 7 late days. Each late day extends the deadline by 24 hours and does not influence the grade. The late days can be used for homeworks and scribing only.
Late submissions turned in after all 7 late days have been exhausted will not be evaluated and will receive 0 points.
Academic Integrity
Please read UMBC's policy on Academic Integrity.
I take academic integrity seriously. I hope that we will never have to deal with violations -- they are never pleasant for anyone involved.
Please read the policies stated in the Syllabus .