Welcome to the homepage of the lecture

Image Processing and Computer Vision

Winter term 2011 / 2012

Image Processing and Computer Vision

Prof. Joachim Weickert
Office hour: Tuesday, 14:15 - 15:15.

Coordinator of tutorials: Laurent Hoeltgen

Winter Term 2011 / 2012

Lectures (4h) with theoretical and programming assignments (2h);
(9 ETCS points)

Lectures: Tuesday and Thursday, 10-12 c.t., Building E1.3, Lecture Hall 002

First lecture: Tuesday, October 18, 2011

Tutorials: 2 hours each week; see below.

NEWS: The distribution of places for the second exam are now online.

Opportunity for exam inspection:
Fridaz, April 13, 2:00 pm - 3:00 pm, Room 4.10, Bld. E1 7

NEWS: The results of the second written exam are now online.

Type of Lectures – Prerequisites – Tutorials – Registration – Written Exam – Contents – Material for the Programming Assignments – Literature

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.

The lectures are continued in the summer term by the course "Differential Equations in Image Processing and Computer Vision" which leads to current research topics. Both courses are necessary in order to pursue a master'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 have questions concerning the tutorials, please do not hesitate to contact Laurent Hoeltgen. The tutorials are conducted by Nicolas Becker, Madina Boshtaeva, Sven Grewenig, David Hafner, and Laurent Hoeltgen.

Seven groups are scheduled for Tuesday and Wednesday afternoon:

• Group T1:
  Tue, 14-16, Building E1.3, Seminar Room 016
  Tutor: David Hafner


• Group T2:
  Tue, 16-18, Building E1.3, Seminar Room 016
  Tutor: Nicolas Becker


• Group T3:
  Tue, 16-18, Building E2.5, Seminar Room 2 (U36)
  Tutor: Laurent Hoeltgen


• Group W1:
  Wed, 14-16, Building E1.3, Seminar Room 015
  Tutor: Sven Grewenig


• Group W2 (also for honour's programme):
  Wed, 14-16, Building E1.3, Seminar Room 016
  Tutor: Pascal Peter


• Group W3 (in English only):
  Wed, 16-18, Building E1.3, Seminar Room 015
  Tutor: Madina Boshtaeva


• Group W4 (in German):
  Wed, 16-18, Building E1.3, Seminar Room 016
  Tutor: Pascal Peter

If you have difficulties with the programming assignments, feel free to participate in

• Optional Guided Programming (OGP):
  Tue, 18-20, Building E1.3, CIP Room 012
  Tutor: Laurent Hoeltgen

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, w3, w4, and ogp, respectively.

Registration is closed. It was open from Tue, Oct. 18, 2011, 3 pm until Fri, Oct. 21, 2011, 3 pm. You can now check which group you are finally in.

The first written exam takes place on
Tuesday, February 14, 2012 from 14:00 to 17:00,
in Building E2.2, AudiMO, and Building E1.3, Lecture Halls 001-003.

The second written exam takes place on
Tuesday, April 3, 2012 from 14:00 to 17:00,
in Building E2.2, AudiMO, and Building E1.3, Lecture Halls 001-003.

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.

Please check here whether you are admitted to the written exam. If you think that there is an error, please contact as fast as possible Laurent Hoeltgen.

These are the rules during the exams:

• You can use the course material (including lecture notes and example solutions from this web page) and hand-written notes from this semester, but neither books nor any other printed material. Dictionaries are permitted.
• Pocket calculators are not allowed.
• Mobile phones, PDAs, laptops and other electronic devices have to be turned off.
• Please keep your student ID card ready for an attendance check during the exam.
• Solutions that are written with pencil will not be graded.
• You are not allowed to take the exam sheets with you.
• You must stay until the exam is completely over.

Here is the distribution of places by family name (i.e. surname, last name) for the first exam that takes place on Tuesday, February 14, 2012 from 2:00 to 5:00 pm:

Students A - R: Audimo in Building E2.2
Students S - Z : Lecture Hall 002 in Building E1.3

Please do not forget to bring your student ID card with you.

Here is the distribution of places by family name (i.e. surname, last name) for the second exam that takes place on Tuesday, April 3, 2012 from 2:00 to 5:00 pm:

Students A - R: Audimo in Building E2.2
Students S - Z : Lecture Hall 002 in Building E1.3

Please do not forget to bring your student ID card with you.

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 3.06 in Bldg. E1.1 on Thursday, February 23th, 2012, from 2:00 pm to 3:00 pm

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 Bldg. E1.7 on Friday, April 13th, 2012, from 2:00 pm to 3:00 pm

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
18.10.	Foundations I: Definitions, Image Types, Discretisation
20.10.	Foundations II: Degradations in Digital Images (contains classroom assignment C1 and homework H1)
25.10.	Foundations III: Colour Perception and Colour Spaces
27.10.	Image Transformations I: Continuous Fourier Transform (contains classroom assignment C2 and homework H2)
31.10.	Image Transformations II: Sampling Theorem and Discrete Fourier Transform
03.11.	Image Transformations III: Discrete Cosine Transform and Image Pyramids (contains classroom assignment C3 and homework H3)
08.11.	Image Transformations IV: Discrete Wavelet Transform
10.11.	Image Compression (contains classroom assignment C4 and homework H4)
15.11.	Image Interpolation

PART II: IMAGE PROCESSING

Date	Topic
17.11.	Point Operations (contains classroom assignment C5 and homework H5)
22.11.	Linear Filters I: System Theory
24.11.	Linear Filters II: Edge Detection (contains classroom assignment C6 and homework H6)
29.11.	Linear Filters III: Multichannel Edges, Corners
01.12.	Nonlinear Filters I: Morphology and Median Filters (contains classroom assignment C7 and homework H7)
06.12.	Nonlinear Filters II: Wavelet Shrinkage, Bilateral Filters, NL-Means
08.12.	Nonlinear Filters III: Nonlinear Diffusion Filtering (contains classroom assignment C8 and homework H8)
13.12.	Global Filters I: Discrete Variational Methods
15.12.	Global Filters II: Continuous Variational Methods (contains classroom assignment C9 and homework H9)
20.12.	Global Filters III: Deconvolution Methods
22.12.	Texture Analysis (contains classroom assignment C10 and homework H10)

PART III: COMPUTER VISION AND IMAGE UNDERSTANDING

Date	Topic
10.01.	Segmentation I: Classical Methods
12.01.	Segmentation II: Optimisation Methods (contains classroom assignment C11 and homework H11)
17.01.	Image Sequence Analysis I: Local Methods
19.01.	Image Sequence Analysis II: Variational Methods (contains classroom assignment C12 and homework H12)
24.01.	3-D Reconstruction I: Camera Geometry
26.01.	3-D Reconstruction II: Stereo (contains classroom assignment C13 and homework H13)
31.01.	3-D Reconstruction III: Shape-from-Shading
02.02.	Object Recognition I: Hough Transform and Invariants
07.02.	Object Recognition II: Eigenspace Methods
09.02.	Summary, Conclusions, Outlook

Here you can download material for the programming assignments.

Date	Topic
20. 10.	Assignment H1: Noise, Quantisation and Dithering
27. 10.	Assignment H2: Colour Spaces and Subsampling
03. 11.	Assignment H3: Fourier Analysis
10. 11.	Assignment H4: Discrete Cosine Transform
17. 11.	Assignment H5: Point Transformations
24. 11.	Assignment H6: Canny Edge Detector
01. 12.	Assignment H7: Morphology
08. 12.	Assignment H8: NL-Means
15. 12.	Assignment H9: Whittaker-Tikhonov Regularisation, Unsharp Masking
22. 12.	Assignment H10: Deconvolution
12. 01.	Assignment H11: Toboggan Watershed Segmentation
19. 01.	Assignment H12: Optic Flow
26. 01.	Assignment H13: Correlation-Based Stereo Method

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, 2006.
• 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

• E. Trucco, A. Verri: Introductory Techniques for 3-D Computer Vision. Prentice Hill, Upper Saddle River, 1998.
• R. Klette, K. Schlüns, A. Koschan: Computer Vision: Three-Dimensional Data from Images. Springer, Singapore, 1998.
• R. Szeliski: Computer Vision: Algorithms and Applications. Springer, New York, 2010.

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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