This course is suited for undergraduate or graduate Engineering students with a basic knowledge of linear algebra and programming.
Linear Algebra, Basic programming knowledge in MATLAB and Python.
The course does not have an required textbook, however additional references are recommended to supplement the lecture notes:
- Computer Vision: Algorithms and Applications: Book Online
- Computer Vision a Modern Approach, Forsyth and Ponce, Prentice Hall, 2003. (a complete textbook on computer vision)
- Vision Science: Photons to Phenomenology, Stephen Palmer. (a great book to read)
Related Courses & Tutorials
- Alyosha Efros (CMU), Computational Photography
- Bastian Leibe (rwth-aachen), Computer Vision
- Li Fei-Fei (Stanford), Rob Fergus (NYU), Antonio Torralba (MIT), Recognizing and Learning Object Categories
- David Fleet (U. Toronto), Foundations of Computer Vision
1 Homework and 3 Projects 60%, Midterm 20%, Final Project 20%.
Students will have total of 5 late days to use during the semester. These late days are used to submit homeworks/projects after the due date with no penalty.
- We will be using MATLAB and Python for the course. However, the final project can be done using only Python.
- MATLAB is free for SEAS students. More details about downloading MATLAB on your personal computer can be found at https://www.seas.upenn.edu/cets/software/matlab/. This is recommended, although MATLAB can be used on SEAS computers throughout campus as well.
You are allowed and encouraged to work together on projects with at most one other student. However, there will be no collaboration on the homeworks. Any discussions on the homeworks must be cited.
The 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.