Introduction to Computer Vision
    CS4670/5670, Fall 2013

Time: MWF 10:10am - 11:00am
Place: Phillips 101 (map)

Instructor: Noah Snavely (snavely@cs.cornell.edu)
    office: Upson 4157
    office hours: Wednesdays 1:30-3pm

TAs (TA office hours held in Upson 317):
Daniel Hauagge (hauagge@cs.cornell.edu)
    office hours: W 4:30-5:30, Th 2:30-4
Scott Wehrwein (swehrwein@cs.cornell.edu)
    office hours: Th 1:00-2:30
Gagik Hakobyan (gh328)
    office hours: M 4-5:30, Th 4-5:30
Jeremy Feinstein (jlf248)
    office hours: M 11:30-1, W 11-12:30
Ronnie Bunshaft (rlb282)
    office hours: T 1:30-3, W 12-1:30

Questions? Visit the CS4670 page on Piazza.
  Lectures Projects Class Resources  

The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include reconstructing the 3D shape of an environment, determining how things are moving, and recognizing people and objects and their activities, all through analysis of images and videos.

This course will provide an introduction to computer vision, with topics including image formation, feature detection, motion estimation, image mosaics, 3D shape reconstruction, and object and face detection and recognition. Applications of these techniques include building 3D maps, creating virtual characters, organizing photo and video databases, human computer interaction, video surveillance, automatic vehicle navigation, and mobile computer vision. This is a project-based course, in which you will implement several computer vision algorithms throughout the semester.

Prerequisites

This course will be self-contained; students do not need to have computer vision background. However, the following are required:

  • Data structures
  • Working knowledge of C/C++
  • Linear algebra
  • Vector calculus
Please send the instructor email or speak to me if you are unsure of whether you can take the course.

Textbook

This course will have readings from Computer Vision: Algorithms and Applications (online), by Richard Szeliski.

Online Discussion

This class uses Piazza for discussions and announcements. Grades will be posted on CMS.

Honesty and Integrity Policy

Projects are to be done either individually or in groups of two, as specified in the project description. You may collaborate on the whiteboard, but each group's code must be their own.