Welcome to
CIS 580 - 2022 Spring
Term: Spring 2022
Place: Wu and Chen Auditorium
https://upenn.zoom.us/j/93817327461 or through Canvas
Time: Monday & Wednesday, 12:00 PM - 1:30 PM
( first class 1/12)
Course Instructor
Dr. Kostas Daniilidis
Email: kostas@cis.upenn.edu
Office: 472 Levine Hall
Office Hours: 1:30-3p Mondays in person (outside Levine 472)
Course Description
CIS580 is an introduction to the problems of computer vision and machine perception that can be solved using geometrical approaches rather than statistical methods, with emphasis on analytical and computational techniques. This course is designed to provide students with an exposure to fundamental mathematical and algorithmic techniques that are used to tackle challenging image-based modeling problems. The content of this course finds application in the fields of Artifical Intelligence and Robotics. Some of the topics that are covered are: Signal processing, projective geometry, camera calibration, image formation and transformations, computational stereopsis, and structure from motion.
Prerequisites: No prior experience with computer vision is assumed, however the following skills are necessary for this class: Mathematics (Linear algebra, vector calculus, and probability), data structures (representing images as features and geometric constructions) and programming.
Textbook References:
Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman (optional)
Grading Policy:
Homework: 60%, Midterm 1: 20%, Midterm 2: 20%
Late Policy: 5 total late HW days without penalty for the semester
Piazza: Link
Last year's website: CIS 580 Spring 2021
Office Hours
We will be using OHQ.io to manage office hours. To join this course's OHQ, visit https://ohq.io/ where you will be prompted to sign in via Penn WebLogin. Then, join a new course and pick CIS 580 from the drop down.
When the office hours start, the queue ``Office Hours" will open and you will be able to add yourself in. We will try to monitor Piazza during OH so if you have a problem signing in or accessing the queue let us know (or you can even join the zoom call and ask us there). The queue is mainly to keep track of who is going next. Many times it is better to talk about questions in a group setting so we will do that. Also, only check for a queue during the scheduled TA office hours as indicated below.
Link to course OHQ: Here
Teaching Assistants
Leon Kim
Email: leonmkim@seas.upenn.edu
Office Hour: 8-9PM Mondays
4th Floor Levine Hall Bump Space (unless announced otherwise on Piazza)
Katrina Ashton
Email: kashton@seas.upenn.edu
Office Hour: 3-4PM Wednesdays (Starting 01/26)
Jiahui Lei
Email: leijh@seas.upenn.edu
Office Hour: 1-2PM Thursdays
4th Floor Levine Hall Bump Space
The in-person questions will be handled first
Wen Jiang
Email: wenjiang@seas.upenn.edu
Office Hour: 2-3PM Thursdays (Starting 01/27)
Claude (Ziyun) Wang
Email: ziyunw@seas.upenn.edu
Office Hour: 5:15-6:15 PM Tuesdays
Code of Academic Integrity
University of Pennsylvania's CIS department encourages collaboration among graduate students. However, it is important to recognize the distinction between collaboration and cheating, which is prohibited and carries serious consequences. Cheating may be defined as using or attempting to use unauthorized assistance, material, or study aids in academic work or examinations. Some examples of cheating are: collaborating on a take-home exam or homework unless explicitly allowed; copying homework; handing in someone else's work as your own; and plagiarism. Any student suspected of cheating will be reported to the Office of Student Conduct.