1 Computational Vision CSCI 363, Fall 2012 Lecture 1 Introduction to Vision Science Course webpage:

2 Course Description Course Webpage: Computational vision: Combines information from mathematics, computer science and neuroscience. Aims to understand how a machine or biological visual system works. Goals of the course: Provide an introduction to the algorithms underlying machine and biological visual systems. Examine the processes involved in converting a 2-dimensional image to a 3- D representation of the physical world. Compare computational models of visual processing with physiological and psychophysical results from human and other biological visual systems.

3 Topics The topics covered include: edge detection spatial frequency analysis of images stereopsis motion computation color object recognition

4 Important Things to Know Course Webpage: Textbook: Vision Science. Photons to Phenomenology, by Stephen Palmer. There will be additional readings handed out in class. Midterm Exams: Wednesday, September 26, 6:30 – 8:30 p.m. Wednesday, October 17, 6:30 – 8:30 p.m. Final Project: There will be a final project, but no final exam

5 Grading Grading Policy: Participation: 15% Homework: 25% Midterm 1: 20% Midterm 2: 20% Final Project: 20% Late Policy: 10% off of your grade per day late.

6 Collaboration Working with others: You may discuss strategies for solving homework problems. You must write up and turn in your own work. You must write the names of people you worked with on your assignment. Consulting outside sources: You may consult the internet or published sources of information. You must cite each source of ideas you adopt.