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CS484: Introduction to Computer Vision

Fall 2018

 

Instructor

Min H. Kim, [Room] 3429, [email]

Course Description

 

This course provides a comprehensive introduction to computer vision, including the foundations of camera image formation, geometric optics, feature detection, stereo matching, motion estimation, image recognition, scene understanding, etc. This course will help students develop intuitions and mathematics of various computer vision applications.

Time and Place

Monday and Wednesday 1:00PM—2:30PM, Rm. 111, Bldg. N-1

Teaching Assistants

Suk Jun Jeon, [e-mail]
Hyunho Ha, [e-mail]
Hyeonjoong Jang, [e-mail]

Main Textbook

Richard Szeliski (2010) Computer Vision: Algorithms and Applications, Springer [site]

Prerequisites

There are no official course prerequisites.

Course Goal

Student will establish theoretical and practical foundations of computer vision and be familiar with various computer vision applications.

Tentative Schedule

 
  Week Date Lecture   Slides Assignments
  1 08/27 Introduction to computer vision    
    08/29 Image formation (1)    
  2 09/03 Image formation (2)    
    09/05 Color (1)  
  3 09/10 Color (2)    
    09/12 Image enchancement    
  4 09/17 Signal processing    
    09/19 Spatial filters (1)  
  5 09/24 Mid-Authumn Festival Days    
  6 10/01 Spatial filters (2)      
    10/03 Feature detection (1)    
  7 10/8 Feature detection (2)    
    10/10 Morphological image operations (1)    
  8 10/15 Mid-term exam (TBA)      
  9 10/22 Morphological image operations (2)    
    10/24 Frequency domain processing (1)    
  10 10/29 Frequency domain processing (2)    
    10/31 Noise reduction  
  11 11/05 Image restoration    
    11/07 Image transformation (1)    
  12 11/12 Image transformation (2)    
    11/14 Multi-resolution processing      
  13 11/19 3D stereo imaging (1)    
    11/21 3D stereo imaging (2)  
  14 11/26 3D surface reconstruction      
    11/28 Supervised learning-based recognition    
  15 12/03 Representation-based image reconstruction    
    12/05 No lecture (SIGGRAPH Asia 2018)    
  16 12/10 Final exam (TBA)      
             

Grading

Attendance (10%), midterm/final exams (50%), assignments (30%), quizzes (10%)

Resources

Computer Graphics papers
Computer Vision papers

http://kesen.realtimerendering.com/
http://www.cvpapers.com/

Hosted by Visual Computing Laboratory, School of Computing, KAIST.

KAIST