Image & Video Processing - Concepts and Techniques (Sommersemester 2022)
Lecturer:
Dr. Matthias Trapp
(Computergrafische Systeme)
,
Max Reimann
(Computergrafische Systeme)
,
Sumit Shekhar
(Computergrafische Systeme)
General Information
- Weekly Hours: 4
- Credits: 6
- Graded:
yes
- Enrolment Deadline: 01.04.2022 - 30.04.2022
- Examination time §9 (4) BAMA-O: 28.07.2022
- Teaching Form: Lecture / Exercise
- Enrolment Type: Compulsory Elective Module
- Course Language: German
Programs, Module Groups & Modules
- HCGT: Human Computer Interaction & Computer Graphics Technology
- HPI-HCGT-K Konzepte und Methoden
- HCGT: Human Computer Interaction & Computer Graphics Technology
- HPI-HCGT-T Techniken und Werkzeuge
- HCGT: Human Computer Interaction & Computer Graphics Technology
- HPI-HCGT-S Spezialisierung
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-K Konzepte und Methoden
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-T Techniken und Werkzeuge
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-S Spezialisierung
- PREP: Data Preparation
- HPI-PREP-K Konzepte und Methoden
- PREP: Data Preparation
- HPI-PREP-T Techniken und Werkzeuge
- PREP: Data Preparation
- HPI-PREP-S Spezialisierung
- SCAL: Scalable Data Systems
- HPI-SCAL-K Konzepte und Methode
- SCAL: Scalable Data Systems
- HPI-SCAL-T echniken und Werkzeuge
- SCAL: Scalable Data Systems
- HPI-SCAL-S Spezialisierung
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-C Concepts and Methods
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-T Technologies and Tools
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-S Specialization
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-C Concepts and Methods
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-T Technologies and Tools
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
Description
This course teaches fundamentals of image and video processing techniques and data representations with selected applications to image and video enhancment and stylization as well as video summarization. Concepts and implementation of processing techniques are part of the lectures and exercises. Course topics include (among others):
- Introduction to Image and Video Processing
- Signal Processing and Sampling
- Point-based Processing Operation
- Neighborhood-based Processing Operations
- Global Processing Operations
- Hardware-accelerated Optimization Techniques
- Deep Neural Networks for Image and Video Transformations
- Image and Video Stylization
- Video Summarization
Requirements
There are no formal requirements. Successful participation of 3D Computergrafik I+II lectures as well as knowledge of OpenGL and the OpenGL Shading Language is beneficial.
Literature
A script will be published for the lecture, which will be made available in the Moodle system (https://moodle.hpi3d.de) to accompany the lecture.
Learning
Examination
- Depending on the number of participants: oral or written exam at the end of the course.
- The final grade is constituted by the exercise grade (25%) and the exam grade (75%).
- We plan 3 to 4 exercises.
- The performance recording process begins with the submission of the first exercise sheet.
- If students choose to work in a group (maximum 2 students), the group will receive an overall grade, rather than individual grades for each student.
Dates
- Monday, 09:15 - 10:45, A1.2
- Wednesday, 13:30 - 15:00, HS 3
- First session will be at 20.04.2022, 13:30, HS3
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