Welcome to

CIS 580 - 2023 Spring

Term: Spring 2023

Place: Levine Hall 101

No Zoom but Panopto recordings available.

Time: Monday & Wednesday, 12:00 PM - 1:30 PM
( first class 1/11)

Course Instructor

Dr. Kostas Daniilidis

Email: kostas@cis.upenn.edu

Office: 472 Levine Hall

Office Hours: Wed 1:30-3p (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)

Elements of Geometry for Computer Vision and Computer Grahics by Tomas Pajdla

Grading Policy:

Homework: 60%, Midterm 1: 20%, Midterm 2: 20%

Late Policy: 5 total late HW days without penalty for the semester

This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com.Find our class signup link at: https://piazza.com/upenn/spring2023/cis5800

Last year's website: CIS 580 Spring 2022

Office Hours

Kostas Daniilidis: Wed 1:30 - 3:00pm (outside Levine 472)

Anthony Bisulco: Mon 1:30 - 2:30pm (outside Levine 472)

Agelos Kratimenos: Mon 5:00 - 6:00pm (Levine 4th floor bump space)

Malakhi Hopkins: Wed 4:00 - 5:00pm (Zoom)

Yufu Wang: Thur 1:30 - 2:30pm (Levine 4th floor bump space)

Teaching Assistants

Anthony Bisulco

Email: abisulco@seas.upenn.edu

Agelos Kratimenos

Email: agelosk@seas.upenn.edu

Malakhi Hopkins

Email: mhopki3@seas.upenn.edu

Yufu Wang

Email: yufu@seas.upenn.edu

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.

Report abuse