Computer Vision Systems, CAP 6411

Fall 2016, Mon and Wed 16:30-17:45, HEC 110 
Office hours: Immediately after the class, or by appointment

General Information:

Instructor: Ali Borji

 Email: aborji at crcv dot ucf dot edu
 Course venue: HEC 110 
 Office phone: 407 823 0667

Note: There has been a slight change in the syllabus of this course. We are working towards making these changes permanent. The process, however, will take some time.

Recommended textbooks:


Basic probability, linear algebra and calculus. Good programming skills.


This course encompasses both human and computer vision topics. We will cover some important topics in vision including image formation, image processing, segmentation, grouping, edge and boundary detection, color perception, object and scene recognition and detection, motion estimation, stereo vision, and structure from motion, deep learning, etc. For each topic, we will first address engineered approaches in computer vision followed by biological vision mechanisms.
This course will offer physiological, psychophysical and computational approaches to understand vision in general (human vision in particular). Students are supposed to relate the two fields together to create a consistent and complete understanding of the process of visual perception. For the physiological approach, the course will introduce the areas of lower level visual processing in the receptors of the eye and the lateral geniculate nucleus and higher level visual processing in different areas of the brain. In the psychophysical approach, the course will introduce the different psychophysical models of human vision, like the models of perceptual organization, perceptual segregation, and construction. Concepts of color, depth, movement and their visual perception will be introduced. In the computational approach, we will study models that aim to explain biological data as well as the state of the art computer vision problems and techniques. To relate the materials presented in the context of different areas of computer science, examples of the quantification and use of these physiological and psychophysical models in computer vision, computer graphics, multimedia and HCI will be referenced.

Course Syllabus

Grading policy

  • Class participation and discussion 10%

  • Two programming homeworks 20%

  • Paper Presentations: 20%

  • Project 50% [project ideas]

Late policy

- 20% off per day (up to 4 days)


  • Major Vision Conferences:
    • Computer Vision and Pattern Recognition (CVPR)
    • International Conference in Computer Vision (ICCV)
    • European Conference in Computer Vision (ECCV)
    • Advances in Neural Information Processing Systems (NIPS)
    • International Conference in Learning Representations (ICLR)
  • Major Vision Journals:
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
    • International Journal of Computer Vision (IJCV)
    • IEEE Transactions on Image Processing (TIP)
  • MATLAB Resources:

Other vision resources:

My own vision course at UWM:


The course webpage will be updated regularly throughout the semester with lecture notes, programming and reading assignments and important deadlines. 

Collaboration Policy:

Collaboration policy - Homeworks must be done individually. Each student must hand in their own answers. In addition, each student must write their own code in the programming part of the assignment. It is acceptable, however, for students to collaborate in figuring out answers and helping each other solve the problems. We will be assuming that, as participants in a graduate course, you will be taking the responsibility to make sure you personally understand the solution to any work arising from such a collaboration.


The materials from this class rely significantly on slides prepared Thomas Serre and Elisa Aminov. 

© 2016 Ali Borji, University of Central Florida