CAP5415 – Computer Vision
(3 Credit Hours)
Fall 2021
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Instructor: | Yogesh S Rawat |
Email: | yogesh[at]crcv[dot]ucf[dot]edu (Please put [CAP5415] in the subject line when you email) |
Office: | HEC 241 |
Phone: | 407-823-6495 |
Time: | Tuesdays and Thursdays 4:30 PM to 5:45 PM |
Location: | Remote instruction [Zoom] |
Office Hours: | Tuesday and Thursday 2:00 PM to 3:00 PM and by appointment [Zoom virtual room] |
Teaching Assistant: | Taojiannan Yang |
Email: | taoyang1122@knights.ucf.edu (Please put [CAP5415] in the subject line when you email me) |
Office: | HEC-254 (Computer Vision Lab) |
Phone (Vision Lab): | 407-823-4733 |
Office Hours: | Tuesday and Thursday 3:00 PM to 4:00 PM [Zoom virtual room] |
Course Contents
This introductory course will focus on traditional methods as well as modern deep learning approaches for computer vision. We will cover the fundamentals of imaging geometry, camera modeling and calibration, and image filtering. Following this, we will focus on feature detection, edge detection, image classification, scene understanding, object detection, and optical flow, where we will cover both classical as well as deep learning approaches. At the end of this course, the student will have an in-depth understanding of how computer vision works, design and implement computer vision algorithms, and pursue advanced topics in computer vision research. A tentative list of topics to be covered in this course,
- Mathematical Preliminaries
- Imaging Geometry, Camera models, Coordinate Transforms
- Image Filtering, Edge Detection, Feature Extraction
- Basics of Neural Networks for Pattern Recognition
- Deep Learning for Computer Vision
- Region/Boundary Segmentation
- Image Classification
- Object Detection
- Action Recognition
Zoom
The zoom link for the lecture and office hours will be provided via Webcourses.
This course will use Zoom for synchronous (“real time”) class meetings. Meeting dates and times will be scheduled through Webcourses@UCF and should appear on your calendar.
Please take the time to familiarize yourself with Zoom by visiting the UCF Zoom Guides at <https://cdl.ucf.edu/support/webcourses/zoom/>. You may choose to use Zoom on your mobile device (phone or tablet).
Things to Know About Zoom:
- You must sign into my Zoom session using your UCF NID and password.
- The Zoom sessions are recorded.
- Improper classroom behavior is not tolerated within Zoom sessions and may result in a referral to the Office of Student Conduct.
- You can contact Webcourses@UCF Support at <https://cdl.ucf.edu/support/webcourses/> if you have any technical issues accessing Zoom.
Pre-requisites: Basic Probability/Statistics, a good working knowledge of Python, Linear algebra, Vector calculus.
Programming
Python will be main programming environment for the assignments. Following book (Python programming samples for computer viion tasks) is freely available.
Python for Computer Vision. A tutorial will be given in the class on PyTorch for deep learning.
Collaboration
Students are free to discuss ideas and technical concepts. However, students must submit original work for all assignments, projects and exams, and abide by UCF Golden Rule.
University-Wide COVID-19 guidelines
UCF encourages students, faculty and staff to take positive steps when they see others not complying with the COVID-19 Return to Campus Policy.
The ability to participate in face-to-face classes and activities is dependent upon every member of the campus community adopting simple steps, such as wearing a face covering and physical distancing, outlined in the policy to prevent further spread of the coronavirus. UCF employees and students must complete the COVID Self-Checker each day they will be on campus and prior to their arrival on campus. The COVID Self-Checker can be completed online or through the UCF Mobile app, with the student version of the assessment launching today.
COVID-19 and Illness Notification
Students who believe they may have a COVID-19 diagnosis should contact UCF Student Health Services (407-823-2509) so proper contact tracing procedures can take place.
Students should not come to campus if they are ill, are experiencing any symptoms of COVID-19, have tested positive for COVID, or if anyone living in their residence has tested positive or is sick with COVID-19 symptoms. CDC guidance for COVID-19 symptoms is located here: (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html)
Students should contact their instructor(s) as soon as possible if they miss class for any illness reason to discuss reasonable adjustments that might need to be made. When possible, students should contact their instructor(s) before missing class.
In Case of Faculty Illness
If the instructor falls ill during the semester, there may be changes to this course, including having a backup instructor take over the course. Please look for announcements or mail in Webcourses@UCF or Knights email for any alterations to this course.
Course Accessibility and Disability COVID-19 Supplemental Statement
Accommodations may need to be added or adjusted should this course shift from an on-campus to a remote format. Students with disabilities should speak with their instructor and should contact sas@ucf.edu to discuss specific accommodations for this or other courses.