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TSBB15 Computer Vision VT2021

This course is given during the VT1 and VT2 periods. Note that not all the time slots in the course schedule will be used. A few spare slots have been reserved in case a lecture has to be moved. The actually planned lectures are listed below on this page, and any changes to this plan will be announced during the lectures, and on this page.

Registration

If you intend to take the course but are not registered, make sure to register ASAP in Ladok, using the Student portal. You need to be registered on the course to receive course email, and to have results registered in Ladok. If you take the course but are not registered to any program at Linköping University, please contact the course examiner in order to make sure that you receive email about the course.

Course extent

This course is worth 12 ECTS credits, which corresponds to approximately 320h of work per student. The time is divided among the following activities:

More details can be found in Studieinfo (the web interface to the Bilda course database).

People

We all have our offices in the B-building, ground floor. Teacher offices are in corridor D (rooms 2D:513 to 2D:527), assistant offices are in Visionen. We recommend the use of email to request meetings.

Literature

In the course we will mainly use the following two books:

  1. Richard Szeliski, Computer Vision: Algorithms and Applications, Springer Verlag (2011).
    This book covers topics such as tracking, optical flow and image features.
    The book is available as an on campus e-book via the LiU library. See also Book webpage.
  2. Klas Nordberg, Introduction to Representations and Estimation in Geometry (IREG).
    This compendium covers only the 3D geometry part of the course.

Other topics covered in the course, such as background models are missing from these two. For side reading on other topics, we have collected pointers to relevant literature in the column "Material" in both of the "Lecture and Lab schedules" below. A few texts are in the course TSBB15 GIT repository.

Examination

The course has a written examination which is offered at three occasions during 2021 (see Tentabokning):
  • 2021-03-23, 14-18: Re-examination opportunity for last year's students (TEN1), and voluntary mid-term examination for this years's students (KTR1).
  • 2021-06-01, 14-18: Examination at end of course.
  • 2021-08-17, 8-12: Re-examination opportunity. Note: this exam will be on site.

The Lisam course room for 2021.

Old exams

The exams from 2018, 2019 and 2020 in TSBB15 can be found here.

How to use the old exams: We recommend that you use these exams as pointers into the literature ("instuderingsfrågor"). To answer the exam, read corresponding discussions in your notes, the course book, and the lecture slides. While it is faster to look at other people's exam answers, this merely gives you answers, while reading and thinking also results in understanding.

Grades

How to pass the course, and the grading criteria are described here.

Lecture and lab schedule VT1

  • The course schedule for TSBB15 can be found in TimeEdit.
  • A more detailed schedule for VT1, with reading material is given below.
    The course content is similar to last year's course, so you may want to look there for details (e.g. slides). Updated slides for this year will be added below, after each lecture.
Date,Time,Room Activity Teacher Material
Jan 20: 10.15-12
Zoom
MeetingID:
619 2184 1348
Lecture 1
Introduction to Computer Vision
Per-Erik
Jan 21: 13.15-17
OLYM
Computer lessons 1&2
Images in Python
Gustav
Jan 22: 10.15-12
Zoom
MeetingID:
619 7833 0323
Lecture 2
Image Representations
Mårten
Jan 27: 10.15-12
Zoom
MeetingID:
619 7833 0323
Lecture 3
The structure tensor
Mårten
Jan 28: 13.15-15
Zoom
MeetingID:
619 7833 0323
Lecture 4
Motion estimation and optical flow
Mårten
Jan 29: 10.15-12
Zoom
MeetingID:
619 7833 0323
Lecture 5
Global motion estimation and tracking
Mårten
Feb 2: 8.15-10
ASGÅRD
Computer exercise 1
Tracking
Preparation
time
Feb 3: 10.15-12
Zoom
MeetingID:
619 2184 1348
Lecture 6
Clustering and learning
Per-Erik
Feb 4: 13.15-17
OLYM
Computer exercise 1
Tracking
Zahra, Johan
Feb 5: 10.15-12
Zoom
MeetingID:
619 2184 1348
Lecture 7
Overview of project 1: Tracking
Per-Erik
Feb 9: 8.15-10
OLYM
Computer exercise 1
Followup
Preparation
time
Opportunity to prepare CE1 for approval in case you did not finish yet.
Feb 10: 10.15-12
Zoom
MeetingID:
619 2184 1348
Lecture 8
Local Features
Per-Erik
Feb 11: 13.15-17.00
ASGÅRD
CE1/CE2
Followup and preparation time
Zahra, Johan Extra opportunity to demonstrate CE1 to the Teaching Assistants.
When you are done with CE1 you can prepare for CE2 here.
Feb 18: 13.15-17.00
OLYMPEN
Computer exercise 2 Zahra, Johan
Feb 19: 10.15-12
Zoom
MeetingID:
619 2184 1348
Lecture 9
Biological Vision
Systems
Per-Erik
Mar 5: 10.15-12
Zoom
Lecture 10
Geometry recap, ML, and RANSAC
Mårten
  • Slides for Lecture 10
  • IREG: 10.3 (F), 12.6 (ML), 16.1.3 (opt.tri.), 17 (robust)
  • CVAA: 6.1.4 (ransac)
  • SHB: 10.2 (ransac)
  • HZ: 4.7 (robust), 11.4 (geometric distances)

Lecture and lab schedule VT2

  • The course schedule for TSBB15 can be found in TimeEdit.
  • A more detailed schedule for VT2, with reading material is given below.
    The course content is similar to last year's course, so you may want to look there for details (e.g. slides). Updated slides for this year will be added below, after each lecture.
Date,Time,Room Activity Teacher Material
Mar 29: 10.15-12
Zoom
Lecture 11
RANSAC, Calibrated geometry and PnP
Mårten
Mar 30: 13.15-16
Zoom
Seminar 1
Presentation of project 1
Per-Erik
Apr 6: 13.15-15
Zoom
Lecture 12
Structure from motion, and Project 2
Per-Erik
Apr 8: 8.15-10
Zoom
Lecture 13
Discrete Optimization
Michael
Apr 12: 10.15-12
OLYM
Computer Exercise 3
Optimisation
Preparation
time
Apr 13: 17.15-21
OLYM
Computer Exercise 3
Optimisation
Zahra, Johan
Apr 15: 8.15-10
Zoom
Lecture 15
Image Denoising and Enhancement
Michael Felsberg
Apr 19: 10.15-12

OLYM
Computer Exercise 4
Image Restoration
Preparation
time
Apr 20: 13.15-17

OLYM
Computer Exercise 4
Image Restoration
Preparation
time
Apr 26: 10.15-12
Zoom
Lecture 14
Multiview Stereo
Per-Erik Forssén
Apr 27: 13.15-17
NB! Moved.

OLYM
Computer Exercise 4
Image Restoration
Zahra, Johan
May 3: 10.15-12
Zoom
Guest Lectures
Martin Svensson(Spotscale)
Andreas Wrangsjö(SICK IVP)
May 25: 13.15-16
Systemet
Seminar 2
Presentation of project 2
Per-Erik

Projects

The two projects are conducted in groups of 5, 4 or 3 students (in order of preference). We aim for 5 project groups this year. Assignment into groups is made on the introductory lecture for project 1.

List of project groups VT2021

  • Project 1: Tracking
    Introductory lecture on February 5
    Design plan due February 12
    Report due March 25 (checked by guide before that)
    Presentation seminar on March 30
  • Project 2: 3D Reconstruction
    Introductory lecture on April 6
    Design plan due April 14
    Report due May 20 (checked by guide before that)
    Presentation seminar on May 25

General resources

We suggest and allow you to use the following software:

  • OpenCV (Open Source Computer Vision). Version 3.4.3 is installed on the department's Linux computers (first you need to issue the module add prog/opencv/3.4.3 command). See also the minimal example OpenCV progam (contributed by Gustav Häger).
    Read the section on OpenCV in the hints and pitfalls page. There is a cheat sheet for OpenCV. An important exception is the Background modelling with mixtures of Gaussians, which you are NOT allowed to use (as you're supposed to learn this in the course).
  • Python with OpenCV bindings. Python 3.6.9 is installed in the computer labs. Essential libraries such as Matplotlib, NumPy, and SciPy are also available.
  • VLFeat has a a useful code library, both for Matlab and C/C++. For example, it has an alternative implementation of SIFT, and also an implementation of MSER. Both are made by Andrea Vedaldi.
  • The Visual Geometry Group at Oxford University maintains code for affine invariant region detectors, produced in cooperation with other groups.
  • The Computer Vision Laboratory at ETH provides an implementation of SURF.
  • An IDE, e.g. PyCharm community edition, which is installed in the computer labs after loading the right module (see module avail) (remember to say no to creation of a shortcut on /usr/local when you start pycharm).

Project repositories

Project code should be developed under versioning control, with changes tracked according to LiU-ID of the participating group members.

  • Project groups should create their repositories in the LiU Git. Note: this is not GitHub, and GitHub should not be used.
  • Project guides and examiner should be given "reporter" access to the group repositories.

Hints and pitfalls

Based on experience from previous year's projects, we have accumulated a list of hints and pitfalls for the projects. Read them carefully before starting your project work.


Last updated: 2021-08-09