CSC 391/691 Computer Vision

Dr. V. Paul Pauca
office: 235 Manchester Hall
Dr. Rongzhong Li
office: 235 Manchester Hall

Time: M W F 10:00 - 10:50 am
Office Hour: M W F 3:00 - 5:00 pm
Location: Man 229
Calendar | Syllabus


This is a selected topic class for computer vision. In this class you will learn basic concepts of computer vision and their applications. Every concept will be followed by a simple project assignment based on OpenCV-Python.

Every Monday we will have a lab that introduces programming assignments. The hope is that you get an early start to the assignment, rather than rushing it right before the due date.

The detailed schedule can be found in the calendar and syllabus. This page will be updated regularly with announcements and resources that may help you throughout the semester. After grading every assignment, the best assignment will also be posted here for your reference.

General Resources

Here's the link to your textbook: website | PDF

The official webpage for OpenCV (link) will be your primary reference for coding tasks.

For those who may like to apply computer vision in robotics, you may find Raspberry Pi (link) a friendly platform to start with.

Assignment Requirements

Before submitting your assignments, check the following items:
- Put the assignment into a new clean folder.
- Included all dependencies (image, module, etc).
- Check whether your program can run smoothly inside your submitting folder.
- Check your outputs. Are all your resulting images popping up correctly? Have you included title, axis label, colormap, timing, etc?
- Is the result obvious, or needs extra comments that should be printed to the screen or included in your code?


Dec.12: Assignment5 grades out.
Best: Ziqi

Nov.20: Assignment4 grades out.
Best Effect: Blake | Best Structure: Ladd
| Mine

Oct.24: Grades of mid-term exam and assignment3 out.
Best: Blake

Oct.18: Grades of assignment2 out.

Oct. 2: Grades of assignment1 out.
Best: NickLadd | Mine

Sep. 5: Install OpenCV on your computer.

Aug.31: Our class starts TODAY!

Hall of fame

Nick Ladd wins challenge 1: Realtime photo-booth!