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Image Processing and Computer Vision
Summer Term 2017
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Image Processing and Computer Vision
Prof. Joachim Weickert
Office hour: Tuesday, 14:15 - 15:15.
Coordinator of tutorials:
Aaron Wewior
Office hour: Wednesday, 14:15 - 15:15.
Summer Term 2017
Lectures (4h) with theoretical and programming assignments (2h);
(9 ETCS points)
Lectures:
Tuesday, 10-12 c.t., Building E1.3, Lecture Hall 001
Friday, 10-12 c.t., Building E1.3, Lecture Hall 001
First lecture: Tuesday, April 18, 2017
Tutorials: 2 hours each week; see below.
News – Type of Lectures – Prerequisites – Tutorials – Registration – Written Exam – Contents – Self Test – Material for the Programming Assignments – Example Solutions for the Assignments – Literature
12.10.17: The grading scheme for the second exam has been adjusted
10.10.17:
Opportunity for exam inspection:
Thursday, October 12, Room 4.10, Building E1 7, 2:00 p.m. - 3:00 p.m.
10.10.17: The results of the second written exam are now online.
02.10.17: The seating for the second written exam is online!
02.08.17:
Opportunity for exam inspection:
Friday, August 4, Room 4.10, Building E1 7, 2:00 p.m. - 4:00 p.m.
02.08.17: The results of the first written exam are now online.
26.07.17: The seating for the first written exam is online!
24.07.2017: The list of admitted students is online!
21.04.2017: Registration is closed.
18.04.2017: Registration starts on Tuesday, April 18, 2017, 2:00 p.m. and ends Friday, April 21, 2017, 2:00 p.m.
18.04.2017: Registration is opened!
Broad introduction to mathematically well-founded areas of image processing and computer vision. These fields are important in numerous applications including medical image analysis, computer-aided quality control, robotics, computer graphics, multimedia and artificial intelligence. The classes qualify for starting a bachelor's thesis in our group.
This course is suitable for students of visual computing, mathematics, computer science, bioinformatics, computer and communications technology, and physics. It counts e.g. as a visual computing core course within the visual computing programme, an applied mathematics course within mathematics, or a core course (Stammvorlesung) in computer science.
It is based on mathematical knowledge from the first two semesters. For the programming assignments, some elementary knowledge of C is required. The lectures are given in English.
The tutorials include homework assignments (theory and programming) as well as classroom assignments. The programming assignments give an intuition about the way how image processing and computer vision algorithms work, while the theoretical assigments provide additional mathematical insights. Classroom assignments are supposed to be easier and should guide you gently to the main themes.
For the homework assignments you can obtain up to 24 points per week.
Actively participating in the classroom assignments gives you 12 more
points per week, regardless of the correctness of your solutions.
To qualify for both exams you need 2/3 of all possible points.
For 13 weeks, this comes down to 13 x 24 = 312 points.
Working in groups of up to 3 people is permitted, but all persons must be
in the same tutorial group.
If you miss a tutorial because you are sick, you can still get the points
for participation, if you bring a doctor's certificate.
If you have questions concerning the tutorials, please do not hesitate to contact Aaron Wewior.
Six groups are scheduled for Tuesday and Wednesday afternoon:
- Group T1:
Tue, 12-14, Building E1.3, Seminar Room 014
(in German)
Tutor: Aaron Wewior - Group T2:
Tue, 14-16, Building E1.3, Seminar Room 014
(English only)
Tutor: Kireeti Bodduna - Group T3:
Tue, 16-18, Building E1.3, Seminar Room 014
(English only)
Tutor: Jiayi Wang - Group W1:
Wed, 10-12, Building E2.5, Seminar Room 3 (U 11)
(English only)
Tutor: Jón Arnar Tómasson - Group W2:
Wed, 14-16, Building E2.5, Seminar Room 4 (U 16)
Tutor: Tobias Alt - Group W3:
Wed, 16-18, Building E2.5, Seminar Room 4 (U 16)
(English only)
Tutor: Jón Arnar Tómasson
Remarks: All groups except T1 are conducted in English.
Groups marked with "English only" also only accept exercise
submissions in English.
If you have difficulties with the programming assignments, feel free to participate in
- Optional Guided Programming (OGP):
Tue, 18-20, CIP 012 in Building E1.3
Tutor: Kireeti Bodduna
The tutors can be reached via the mail addresses:
ipcv-# -- at -- mia.uni-saarland.de
where # has to be replaced by t1, t2, t3, w1, w2, and w3, respectively.
Between Tue, April 18, 2017, 14:00 and Fri, April 21, 2017, 14:00, you could register for this course. Registration is now closed. You can still check which group you are finally in.
Please register also in the
HISPOS system.
Please note that the HISPOS registration is completely independent
of the lecture registration and is not administered by us.
There will be two written exams, one at the beginning and one at the end of the semester break.
The first written exam takes place on
Tuesday, August 1, 2017 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre,
and Building E1.3, Lecture Hall 002.
The second written exam takes place on
Friday, October 6, 2017 from 14:00 to 17:00,
in Building E2.2, Günter Hotz Lecture Theatre,
and Building E1.3, Lecture Hall 002.
In order to qualify for the exams you need a total amount of 2/3 of all
possible points from the homework and classroom assignments.
In case of qualification, you are allowed to take part in both exams.
The better grade counts, but each exam will count as an attempt
individually.
Please check here whether you are
admitted to the written exam. If you think that there is an error, please
contact
Aaron Wewior immediately.
Here is the distribution of places by family name (i.e. surname, last name)
for the first exam that takes place
on Tuesday, August 1, 2017 from 14:00 to 17:00:
Students A - N: Building E2.2, Günter Hotz Lecture Theatre
Students O - Z: Building E1.3, Lecture Hall 002
If you are unsure, in which lecture hall you belong, you can check on
this detailed list.
For the second exam that takes place on Friday, October 6, 2017 from 14:00 to 17:00, all students will be in Building E2.2, Günter Hotz Lecture Theatre
Both exams will be closed book exams. You will have to follow these rules:
- You are allowed and obliged to bring three things to your desk only: Your student ID card (Studierendenausweis), a ball-pen that has no function other than writing, and a so-called cheat sheet. This cheat sheet is a A4 page with formulas or important equations from the lecture. Please note that the cheat sheet has to be handwritten by yourself. It will be collected at the end of the exam, and you can get it back at the exam inspection.
- Everything else has to be deposited at the walls of the exam hall. In particular, electronic devices (including your cell phone), bags, jackets, briefcases, lecture notes, homework and classroom work solutions, additional handwritten notes, books, dictionaries, and paper are not allowed at your desk.
- Please keep your student ID card ready for an attendance check during the exam.
- Do not use pencils or pens that are erasable with a normal rubber.
- You are not allowed to take anything with you that contains information about the exam. A violation of this rule means failing the IPCV course.
- You must stay until the exam is completely over.
The results of the first written exam can be found here, and the corresponding distribution of points and grades here.
Each student who has participated in the first written exam has the opportunity to inspect his/her graded solutions in room 4.10 in Building E1.7 on Friday, August 4, 2017 from 2:00 p.m. to 4:00 p.m.
The results of the second written exam can be found
here, and the corresponding
distribution of points and grades
here.
Each student who has participated in the second written exam has the opportunity to inspect his/her graded solutions in room 4.10 in Building E1.7 Thursday, October 12, 2017, from 2:00 to 3:00 p.m.
Course material is available on this webpage in order to
support the classroom teaching and the tutorials, not to replace
them. Additional organisational information, examples and explanations
that may be relevant for your understanding and the exam are provided
in the lectures and tutorials. It is solely your responsibility
- not ours - to make sure that you receive this infomation.
PART I: FOUNDATIONS AND TRANSFORMATIONS
| Date | Topic |
|---|---|
| 18.04. | Foundations I: Definitions, Image Types, Discretisation |
| 21.04. |
Foundations II: Degradations in Digital Images (contains classroom assignment C1 and homework H1) |
| 25.04. | Foundations III: Colour Perception and Colour Spaces |
| 28.04. |
Image Transformations I: Continuous Fourier Transform (contains classroom assignment C2 and homework H2) |
| 02.05. |
Image Transformations II:
Sampling Theorem and Discrete Fourier Transform |
| 05.05. |
Image Transformations III:
Discrete Cosine Transform and Image Pyramids (contains classroom assignment C3 and homework H3) |
| 09.05. | Image Transformations IV: Discrete Wavelet Transform |
| 12.05. | Image Compression (contains classroom assignment C4 and homework H4) |
| 16.05. | Image Interpolation |
PART II: IMAGE PROCESSING
| Date | Topic |
|---|---|
| 19.05. | Point Operations (contains classroom assignment C5 and homework H5) |
| 23.05. | Linear Filters I: System Theory |
| 26.05. |
Linear Filters II: Derivative Filters (contains classroom assignment C6 and homework H6) |
| 30.05. | Linear Filters III: Detection of Edges and Corners |
| 02.06. |
Nonlinear Filters I: Morphology and Median Filters (contains classroom assignment C7 and homework H7) |
| 06.06. | Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means |
| 09.06. |
Nonlinear Filters III: Nonlinear Diffusion Filtering (contains classroom assignment C8 and homework H8) |
| 13.06. | Global Filters I: Discrete Variational Methods |
| 16.06. |
Global Filters II: Continuous Variational Methods (contains classroom assignment C9 and homework H9) |
| 20.06. | Global Filters III: Deconvolution Methods |
| 23.06. |
Texture Analysis (contains classroom assignment C10 and homework H10) |
PART III: COMPUTER VISION AND IMAGE UNDERSTANDING
| Date | Topic |
|---|---|
| 27.06. | Segmentation I: Thresholding, Region Growing, Region Merging |
| 30.06. |
Segmentation II: Watersheds and Optimisation Methods (contains classroom assignment C11 and homework H11) |
| 04.07. | Image Sequence Analysis I: Local Methods |
| 07.07. |
Image Sequence Analysis II: Variational Methods (contains classroom assignment C12 and homework H12) |
| 11.07. | 3-D Reconstruction I: Camera Geometry |
| 14.07. |
3-D Reconstruction II: Stereo (contains classroom assignment C13 and homework H13) |
| 18.07. | 3-D Reconstruction III: Shape-from-Shading |
| 21.07. | Object Recognition I: Hough Transform and Invariants |
| 25.07. | Object Recognition II: Eigenspace Methods |
| 28.07. | Summary, Conclusions, Outlook |
The following self-test problem sheet contains 6 problems, which are intended
to be similar in style and difficulty to a 180-minutes written exam.
| Date | Topic |
|---|---|
| 21.07. | Self Test Problem Sheet |
| 21.07. | Self Test Solution |
Here you can download material for the programming assignments.
Here you find example solutions for the assignments.
Sample solutions are only available during the semester.
There is no specific text book for this class, but many of our image processing topics are covered in one of the following books:
- J. Bigun: Vision with Direction. Springer, Berlin, 2010.
- R. C. Gonzalez, R. E. Woods: Digital Image Processing. Addison-Wesley, Third Edition, 2008.
- K. D. Tönnies: Grundlagen der Bildverarbeitung. Pearson Studium, München, 2005.
Computer vision books include
- R. Klette: Concise Computer Vision. Springer, London, 2014.
- R. Szeliski: Computer Vision: Algorithms and Applications. Springer, New York, 2010.
- E. Trucco, A. Verri: Introductory Techniques for 3-D Computer Vision. Prentice Hill, Upper Saddle River, 1998.
These and further books can be found in the mathematics and computer
science library.
Furthermore, there is an interesting
online compendium,
where many researchers have written survey articles.
General information and numerous links can be found at the
Computer Vision Homepage.
If you are looking for a specific reference, check out
Keith Price's Annotated Computer Vision Bibliography.
Many online articles and citations can be extracted from
the CiteSeer webpage.
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