TeachingWs16BasicMathTools

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Basic Mathematical Tools for Imaging and Visualization - IN2124

Administrative Info

Lecture: Dr. Tobias Lasser

Exercises: Nicola Rieke, Anca Stefanoiu


IN2124: 2+2 SWS, 5 ECTS

The lecture is given in English.

Contact

Time & Location

Lecture and exercise:

  • Wednesday, 12:05 - 13:35, room MI HS 2
  • Thursday, 16:00 - 18:00, room MI HS 2

Exam:

  • Wednesday, March 1, 2017, 13:30 - 15:00, Interims Hörsaal 1 and 2
    • Duration: 90 minutes
    • Allowed material: none
    • Exam inspection: Wednesday, April 5, 2017, 14:00 in MI 03.13.010 (registration by email required until April 3, 2017, 11:59!)

Repeat exam:

  • Wednesday, April 19, 2017, 10:30 - 12:00, MI Hörsaal 1
    • Duration: 90 minutes
    • Allowed material: none
    • Exam inspection: Wednesday, May 17, 2017, 09:30 in MI 03.13.008

Site Content

Announcements

  • The list of people receiving the grade bonus is available: bonus.pdf. Please check if this sounds correct to you, and contact us if not (updated: Feb. 1, 2017).

Overview

For the development, but also for the application of many image processing techniques and computer vision algorithms, a deep mathematical understanding is of fundamental importance. This lecture aims to provide interested students with a solid mathematical basis for imaging and visualization applications.

Course Schedule

Date Room Type Lecturer Topic Materials Solutions
Wed Oct. 19, 2016 MI HS 2 L Tobias Lasser Introduction and Overview    
Thu Oct. 20, 2016 MI HS 2 L Tobias Lasser Linear Algebra    
Wed Oct. 26, 2016 MI HS 2 E Nicola Rieke, Anca Stefanoiu      
Thu Oct. 27, 2016 MI HS 2 L Tobias Lasser Linear Algebra    
Wed Nov. 2, 2016 MI HS 2 E Anca Stefanoiu      
Thu Nov. 3, 2016 MI HS 2 L Tobias Lasser Linear Algebra    
Wed Nov. 9, 2016 MI HS 2 E Anca Stefanoiu      
Thu Nov. 10, 2016 MI HS 2 L Tobias Lasser Linear Algebra    
Wed Nov. 16, 2016 MI HS 2 E Nicola Rieke      
Thu Nov. 17, 2016 MI HS 2 L Tobias Lasser Analysis    
Wed Nov. 23, 2016 MI HS 2 E Nicola Rieke      
Thu Nov. 24, 2016 MI HS 2 L Tobias Lasser Analysis    
Wed Nov. 30, 2016 MI HS 2 E Nicola Rieke      
Thu Dec. 1, 2016 MI HS 2 L Tobias Lasser Optimization    
Wed Dec. 7, 2016 MI HS 2     no lecture (Dies academicus)    
Thu Dec. 8, 2016 MI HS 2     no lecture    
Wed Dec. 14, 2016 MI HS 2 E Nicola Rieke      
Thu Dec. 15, 2016 MI HS 2 L Tobias Lasser Optimization    
Wed Dec. 21, 2016 MI HS 2 E Nicola Rieke      
Thu Dec. 22, 2016 MI HS 2 L Tobias Lasser Optimization    
Wed Jan. 11, 2017 MI HS 2 E Anca Stefanoiu      
Thu Jan. 12, 2017 MI HS 2 L Tobias Lasser Probability Theory    
Wed Jan. 18, 2017 MI HS 2 E Anca Stefanoiu      
Thu Jan. 19, 2017 MI HS 2 L Tobias Lasser Probability Theory    
Wed Jan. 25, 2017 MI HS 2 E Nicola Rieke      
Thu Jan. 26, 2017 MI HS 2 L Tobias Lasser Probability Theory    
Wed Feb. 1, 2017 MI HS 2 E Anca Stefanoiu      
Thu Feb. 2, 2017 MI HS 2 L Tobias Lasser Application Examples    
Wed Feb. 8, 2017 MI HS 2 E all Question & Answer session    
Thu Feb. 9, 2017 MI HS 2     no lecture    

Literature

MATLAB

Wolfram Alpha

  • For quickly calculating, plotting, or learning something you might want to have a look at Wolfram Alpha.

Linear Algebra

  • Yousef Saad, Iterative Methods for Sparse Linear Systems, SIAM (You can download the book for free!)
  • Gilbert Strang, Introduction to Linear Algebra, Wellesley-Cambridge Press (Available in the library! Check out his video-lectures on youtube!)
  • Lloyd N. Trefethen and David Bau, Numerical Linear Algebra, SIAM (Available in the library!)

Analysis

  • Walter Rudin, Real and Complex Analysis, McGraw-Hill (Available in the library!)

Optimization

Probability Theory

  • Heinz Bauer, Measure and Integration Theory, deGruyter (Available in the library!)
  • Sheldon Ross, Introduction to probability and statistics for engineers and scientists, Elsevier (Available in the library!)




TeachingForm
Title: Basic Mathematical Tools for Imaging and Visualization
Professor: Tobias Lasser
Tutors: Nicola Rieke, Anca Stefanoiu
Type: Lecture
Information: 2 + 2 SWS, 5 ECTS Credits (IN2124)
Term: 2016WiSe
Abstract: For the development, but also for the application of many image processing techniques and computer vision algorithms, a deep mathematical understanding is of fundamental importance. This lecture aims to provide interested students with a solid mathematical basis for imaging and visualization applications.


Edit | Attach | Refresh | Diffs | More | Revision r1.62 - 17 Oct 2017 - 08:40 - AncaStefanoiu

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