After successful completion of the course, students are able to describe basic concepts of computer graphics and computer vision from both a theoretical and a practical point of view. Students are able to understand the entire process chain up to the image generation.
This lecture is given in German.
* Digital images: Resolution, Sampling, Quantization, Representation of colors
* Image operatons: Point operations, local and global operations
* Segmentation
* Detection of motion
* Representation: contour-based, reggion-based (Moments, Graphs)
* Encoding: Entropy-Encoding, Source-Encoding
* Compression: Predictive encoding, Vector quantization, JPEG, MPEG
* Hardware: Input and output devices, Medical imaging, Sensors
* Radiometric and geometric transformations
* Graphic primitives and their attributes
* 2D and 3D Viewing, Rendering Pipeline
* Visibility
* 3D object representations
* Curves and Surfaces
* Lighting and Shading
* Ray-Tracing und Global Illumination
* Textures and other mappings
* Colors and Color spaces
* Computational photography
* Non-photorealistic rendering
ECTS-breakdown (estimation, advise):
40 h Lectures
42 h Preparation for exams
68 h Assignments
---------------------------------------------
150 h equals 6 ECTS, each of 25 hours
Es gibt ein deutschsprachiges Skriptum, das kapitelweise jeweils zu den Vorlesungseinheiten online gestellt wird, welches über TUWEL zur Verfügung gestellt wird.
Für Abschnitte der Computer Vision Vorlesung wird "Computer Vision: Algorithms and Applications" von R. Szeliski empfohlen (frei verfügbar, siehe Links).
Grundlegende Programmierkenntnisse.
Pythonkenntnisse vorteilhaft, aber nicht notwendig.
