Coursebooks 2017-2018

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Caution, these contents corresponds to the coursebooks of last year


Computer vision

CS-442

Lecturer(s) :

Fua Pascal

Language:

English

Summary

Computer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors. We will focus on images acquired using digital cameras. We will introduce basic processing techniques and discuss their field of applicability.

Content

Introduction

Extracting 2D Features

3D Shape Recovery

Learning Prerequisites

Recommended courses

Foundations of Image Science

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra lectures and programming exercises using matlab.

Assessment methods

With continuous control

Resources

Bibliography

Ressources en bibliothèque
Websites
Moodle Link

In the programs

  • Data Science, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Digital Humanities, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Computer Science, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Communication Systems - master program, 2017-2018, Master semester 2
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Communication Systems - master program, 2017-2018, Master semester 4
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Computer science minor, 2017-2018, Spring semester
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Communication systems minor, 2017-2018, Spring semester
    • Semester
      Spring
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Computer vision
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
Under construction
Lecture
Exercise, TP
Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German