Advanced Image Analysis
Lecturer:
Dr. Pascal Peter
Tutor: Luisa Danalachi
Winter Term 2022
Lecture (2h) with exercises (2h)
6 credit points
Lectures: Tuesday 16-18 c.t.
First Lecture: Tuesday, October 25, 2022
Tutorials: Friday 14-16 c.t.
First Tutorial: Friday, November 11, 2022
Announcements –
Description –
Entrance requirements –
Tutorials –
Exams
Lecture notes/Assignments –
References
For detailed information at a glance, consult our welcome flyer.
7/11/2022 Registration is now closed.
20/10/2022 Registration is now open.
25/08/2022 Website is online. Registration and
more detailed information will available closer to the beginning of
the semester.
In this lecture, we will discuss advanced topics in the fields of image processing
and computer vision. Most of the presented methods fuse the information from several
images in order to produce an enhanced composite image. Examples for such techniques
are super-resolution, high dynamic range (HDR) imaging, tone mapping and
gradient domain techniques.
Example: Freehand High Dynamic Range Imaging
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Exposure series
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Tone mapped HDR reconstruction without and with alignment
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Requires undergraduate knowledge in mathematics (e.g. ''Mathematik
für Informatiker I-III''), and elementary C knowledge. Basic knowledge in
image processing and computer vision is recommendable. The lectures and tutorials
will be given in English.
There are practical and theoretical weekly assignments. They
will be solved in group work during tutorial sessions
and written solutions will be available.
Exam admission requires regular tutorial attendance.
Details can be found in the introductory lecture.
If you have questions concerning the tutorials, please do not hesitate
to contact
Pascal Peter.
There will be two closed book written exams:
The first written exam will take place on Thursday, February 23, 2023
from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
The second written exam will take place on Monday, April 3, 2023
from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
You can find the detailed rules for our exams in
the self test assignment
in the Teams file repository.
You can participate in both exams, and the better grades counts.
Please remember that you have to register online for the exam
in the HISPOS system of the Saarland University.
If you cannot attend the exam, contact Pascal Peter as early as possible.
In case you have proof that you cannot take part for medical reasons or you
have another exam on the same day, we can offer you an oral exam as a replacement.
Note that we need written proof (e.g. a certificate from a physician/Krankenschein)
for the exact date of the exam.
Lecture notes / Assignments
Lecture content in the form slides and assignments are available for
download via Microsoft Teams. Access will be granted after
registration. In addition, you will gain access to pre-recorded
videos from previous semesters.
Note that the initial registration requires manual confirmation and
can thus be delayed a bit.
There is no specific book that covers the complete content of this class.
Many lectures will be based on articles from journals and conferences.
However, the recent book of R. Szeliski covers some of the topics and
additionally summarises most of the intensively studied areas of
computer vision research:
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R. Szeliski: Computer Vision: Algorithms and Applications.
ISBN: 978-1-84882-934-3, Springer, Berlin, 2011.
Note: You can download a PDF version of the book here.
Further references will be given during the lecture.
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