Welcome to

CIS 5800 - 2024 Fall

Term: Fall 2024

Place: Claire Fagin Hall 118

No Zoom but Panopto recordings available on Canvas.

Time: Monday & Wednesday, 12:00 PM - 1:30 PM

Course Instructor

Dr. Kostas Daniilidis

Email: kostas@cis.upenn.edu

Office: 472 Levine Hall

Office Hours: Mon 2-3p (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 with an emphasis on analytical and computational techniques. This course is designed to expose students to fundamental mathematical and algorithmic techniques used to tackle challenging image-based modeling problems. The content of this course finds application in the fields of computer vision and robotics. After taking the class you will have a firm grasp on real world problems involving projective transformations, structure from motion, localization, visual odometry and SLAM.

Prerequisites: No prior experience with computer vision is assumed, however the following skills are necessary for this class: Mathematics (Linear algebra, vector calculus), data structures (representing images as features and geometric constructions) and Python 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:

HW1 Code 10

HW1 Math. 10

HW2 Code. 10

HW2 Math. 10

HW3 15

HW4 Code 15

HW4 Math. 10

Midterm Exam 20

TOTAL 100

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

Office Hours

Kostas Daniilidis: Mon 1:45pm - 3:00pm (outside Levine 472)

Royina Jayanth: Mon 3:30pm - 5:00pm (Levine 512)

Zi-Yan Liu: Tue 9:00am - 10:30am (Levine 5th floor bump space)

Mufeng Xu: Tue 2:30pm - 4:00pm (Levine 512)

Ruijun Zhang: Wed 8:00pm - 9:30pm (Levine 512)

Teaching Assistants

Royina Jayanth

Email: royinakj@seas.upenn.edu

Office Hours:

Mon 3:30pm - 5:00pm

Zi-Yan Liu

Email: lzi@seas.upenn.edu

Office Hours:

Tue 9:00am - 10:30am

Mufeng Xu

Email: mufeng@seas.upenn.edu

Office Hours:

Tue 2:30pm - 4:00pm

Ruijun Zhang

Email: zruijun@seas.upenn.edu

Office Hours:

Wed 8:00pm - 9:30pm

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.

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