Course Syllabus

Vision is arguably the important of all senses, without which our life would be qualitatively different. Computational vision is a scientific discipline which explores and studies vision from a computational point of view both for the algorithmic inference of properties of the world from images, and for explaining and understanding biological, and in particular, human vision. Although vision is immediate, effortless, and (almost) flawless for most people, both tasks are in fact extremely difficult and challenging. This course seeks to provide the fundamentals of computational vision with additional emphasis on biological and human vision. The required background includes calculus, linear algebra, basic probability, basic numerical analysis or equivalent material, and some experience with programming.

topics that will be covered include:

  • Light and the evolution of light capturing devices (eyes, cameras)
  • Computational aspects of the imaging process and image formation
  • Early vision in man and machine
  • Perceptual organization
  • Color
  • Shape inference
  • High level visual processes and object recognition
  • Applications

Grade Components

Grading :
  • Compulsory attendance!
  • 15% Homework assignments
  • 40% Final exam (you must pass the exam in order to pass the course)
  • 40% Final Project
  • 5% Particiation in 1-2 human vision lab sessions

Coursebook Syllabus