Teaching

Summer Term 2018

Notice: this page contains archived contend about past teaching activities. For the most recent information please select the pages for the current semester.

Lecture: Grundlegende Programmiertechniken (German)

Python Logo

V2+U2
Lecture Time & Place: Tue. 10:15-11:45 c.t., LB 107
Instructor: Prof. Dr. J. Krüger
Exercise Time & Place: see LSF
Exercise Supervisors: Contact at gpt@uni-due.de (R. Rothaller & A. Krekhov)
Course Language: German
Audience: Bachelor

Zusammenfassung: Anhand der Programmiersprachen Python 3 und Java werden grundlegende Programmiertechniken besprochen. Inhalte unter anderem - Einführung und grundlegende Struktur von Programmen - Lexikalische Elemente, Datentypen und Variablen, Anweisungen und Kontrollstrukturen - Elementare Datenstrukturen: Mengen, Felder, Listen - Eingabe und Ausgabe mittels Streams - Funktionen und Module - Grundlegende Algorithmen: Suchen und Sortieren - Eingabe/Ausgabe Listen-Abstraktion. Unterschiede Java / Python.

Lecture: Scientific Visualization

V2+U2
Lecture Time & Place: Mon. 10:00-12:00 c.t. LE 120
Instructor: Prof. Dr. J. Krüger
Exercise Time & Place: Mon. 12:00-14:00 c.t. LE 120
Exercise Supervisor: K.-M. Schorer
Course Language: English
Audience: Master

Abstract: The focus of this introductory course is on discussing efficient techniques to visually represent large-scale data sets from simulation and measurement. Starting with a brief introduction on the data generation processes the visualization pipeline, data structures, mapping techniques and special rendering techniques for scientific data will be discussed. Various examples will be given to outline the benefits of visualization techniques in practical applications. A particular focus is put on interactive methods using GPU-based techniques. Topics include:

  • History of Visualization Methods, from ancient wall paintings to GPU accelerated rendering
  • Data Sources
    • Simulation: basics of finite element discretization to GPU-based methods
    • Measurements: physical details of computed tomography to accelerated reconstruction
  • Data Representation: interpolation techniques, from data to meshes
  • Filtering: various filtering methods and their hardware acceleration
  • Scalar Volumes
    • the basics of direct volume rendering
    • GPU accelerated volume rendering I: slicing and ray-casting
    • GPU accelerated volume rendering II: ray guided volume rendering and out-of-core techniques
    • indirect volume rendering
    • unstructured data
  • Flow Visualization
    • glyph based methods
    • geometric methods
    • GPU-based particle tracing
    • texture-based methods I: LIC
    • texture-based methods II: Explicit Frequency Control
    • feature based methods
  • Virtual Reality

Lecture: Advanced Image Synthesis

V3+U1
Lecture Time & Place:
Tue. 14:00-16:00 c.t. LE 120, Thu. 9:00-10:00 c.t. LE 105

Instructor: Prof. Dr. J. Krüger
Exercise Time & Place: Thu. 8:00-9:00 c.t. LE 105
Exercise Supervisor: A. Waschk
Course Language: English
Audience: Master

Abstract: This lecture deals with the fundamentals of photorealistic and interactive image synthesis. In particular, we discuss techniques to achieve interactive frame rates for the realistic rendering of complex models and scenes using GPU accelerated techniques. Selected graphics algorithms and their efficient implementation exploiting state-of-the-art graphics hardware through graphics APIs will be demonstrated. We focus on dedicated parts of the graphics pipeline and we review the functionality provided by consumer class graphics accelerators including programmable vertex-, geometry- and fragment shaders. In addition, we discuss the governing equations in physics based light transport and we demonstrate effective solution methods for the simulation of global illumination. Topics include:

  • Interactive image synthesis
    • Graphics APIs & hardware, OpenGL, DirectX, Vulkan and CUDA
    • Fixed function & programmable graphics pipeline
    • Introduction to General-purpose computation on graphics hardware (GPGPU)
    • Lighting
      • Local lighting models
      • GPU implementation
    • Environment Mapping
    • GPU Shadowing techniques
      • Projective Shadows
      • Shadow Volumes
      • Shadow Maps
    • Transparent Objects:
      • (depth) sorting with implementations on graphics hardware
      • Order independent transparency & depth peeling on GPUs
  • Physics based rendering
    • Radiometric quantities, rendering equation
    • Raytracing / path tracing
    • Radiosity
    • Irradiance volumes
    • Precomputed radiance transfer (PRT)
    • Ambient Occlusion with focus on GPU-based interactive methods
  • Special topics:
    • GPU friendly High quality terrain rendering & synthesis
    • Rendering of fur and hair
    • Scenegraph APIs
    • Acceleration structures and culling techniques
    • Human visual perception and high dynamic range imaging (HDRI)
    • REYES
    • Image compression techniques

Lab Course (Praxisprojekt): Dear Data 1

Kick-off & Registration Meeting: April 10, 13:00 s.t., LE 335
Time & Place: tba
Instructor: A. Krekhov & Prof. Dr. J. Krüger
Course Language: German
Audience: Bachelor

Abstract: In this lab course the participants will learn to gather data and design scientific visualisations using this data. We will use an approach similar to the award winning Dear Data project by Giorgia Lupi and Stefanie Posavec. Given a specific topic each week, participants will have to track their data and custom design a visual representation of their data and present this representation in front of the group at the end of the week.

Lab Course (Praxisprojekt): Dear Data 2

Kick-off & Registration Meeting: April 10, 12:00 s.t., LE 335
Time & Place: tba
Instructor: M. Michalski & Prof. Dr. J. Krüger
Course Language: German
Audience: Bachelor

Abstract: In this lab course the participants will learn to gather data and design scientific visualisations using this data. We will use an approach similar to the award winning Dear Data project by Giorgia Lupi and Stefanie Posavec. Given a specific topic each week, participants will have to track their data and custom design a visual representation of their data and present this representation in front of the group at the end of the week.

Lab Course (Forschungsprojekt): Smart Running

Kick-off & Registration Meeting: April 12, 10:00 s.t., LE 335
Time & Place: Thu. 10:00-12:00 s.t., LE 335
Instructor: A. Schiewe & Prof. Dr. J. Krüger
Course Language: English or German
Audience: Master

Abstract: More and more runners record their runs with fitness trackers, running watches, or smartwatches. In addition to these watch-based sensing devices worn on the wrist there is an increase in other wearable devices and sensors (STRYD, RunScribe, Arion, SHFT IQ) that attempt to support the runner in improving their performance or running technique. In this project we will evaluate fundamental concepts and develop novel interfaces for runners using commercial or self-made sensor prototypes. The implementation of the project can range from the evaluation of interface sketches which require no programming skills to the implementation of real functioning wearable prototypes depending on the skill set and motivation of the participants.

Seminar: How to Deliver an Engaging Speech - Eine Einführung in elementare Vorbereitungs- und Vortragstechniken

Instructors: Prof. Dr. J. Krüger & team
Kick-off & Registration Meeting: Thu. April 12th, 12:00-14:00 c.t., LF 125
Time & Place: Thu. 12:00-14:00 c.t., LF 125
Course Langugage: English or German
Audience: Bachelor & Master

Abstract: In addition to the scientific content in this seminar we will put special emphasis on the presentation. To improve the presentation skills of the participants we will start the seminar with simpe topics, record short talks from each participant, and analyze the presentation. Students then give a seminar talk on their chosen topic.

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