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521466S Machine Vision, 5 ECTS cr 
Code 521466S  Validity 01.01.1950 -
Name Machine Vision  Abbreviation Machine Vision 
Scope5 ECTS cr   
TypeAdvanced Studies Discipline4307 Information Engineering 
TypeCourse   
  Grading1 - 5, pass, fail 
 
   
Unit Computer Science and Engineering DP 

Teachers
Name
Heikkilä, Janne Tapani 

Description
ECTS Credits 

5 ECTS cr

 
Language of instruction 

English

 
Timing 

Spring, period  3.

 
Learning outcomes 

Upon completion of the course the student
1. understands the fundamentals of image acquisition, representation and modeling
2. can utilize elementary methods of machine vision for image recognition problems
3. can use 2D transformations in model fitting and image registration
4. can explain the basics of 3D imaging and reconstruction

 

 
Contents 

1. Introduction, 2. Imaging and image representation, 3. Color and shading, 4. Image features, 5. Recognition, 6. Texture, 7. Motion from 2D image sequences, 8. 2D models and transformations, 9. Perceiving 3D from 2D images, 10. 3D transformations and reconstruction.

 
Mode of delivery 

Face-to-face teaching, homework assignments.

 
Learning activities and teaching methods 

Lectures (20 h), exercises (16 h) and Matlab homework assignments (30 h), self-studying (67 h).

 
Target group 

Computer Science and Engineering students and other Students of the University of Oulu.

 
Prerequisites and co-requisites 

521467A Digital Image Processing or an equivalent course

 
Recommended optional programme components 

521289S Machine Learning. This course provides complementary knowledge on machine learning methods needed in machine vision.

 
Recommended or required reading 

Lecture slides and exercise material. The following books are recommended for further information: 1) Shapiro, L.G. & Stockman, G.C.: Computer Vision, Prentice Hall, 2001. 2) Szeliski, R.: Computer Vision: Algorithms and Applications, Springer, 2011. 3) Forsyth, D.A. & Ponce, J.: Computer Vision: A Modern Approach, Prentice Hall, 2002.

 
Assessment methods and criteria 

The course is passed with final exam and accepted homework assignments.

Read more about assessment criteria at the University of Oulu webpage.

 
Grading 

Numerical grading scale 1-5. Zero stands for a fail.

 
Person responsible 

Janne Heikkilä

 
Working life cooperation 

No.

 


Current and future instruction
Functions Name Type ECTS cr Teacher Schedule
registration period has not begun Machine Vision  Course  Heikkilä, Janne Tapani  07.01.19 -06.03.19

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