Here you can find an overview of the planned contents of the lecture in the summer semester 2022. Lecture slides of the introductory lecture 2022
The lecture is held in German.
All documents will be provided electronic in Moodle.
If you are interested in the lecture, please register for it in Moodlefrom March 8th, 2022! You will receive the password or automatically via eMail or on request via eMail to firstname.lastname@example.org. Moodle registration is a prerequisite for participation.
Target group and requirements
Master students of the faculties IA, EI, MB as single course or in modules on image processing, 3D vision, technical recognition or optronics. MA students with an interest in 3D image processing as a supplement or to round off their studies.
Good knowledge of physics, mathematics and information or communications technology is helpful.
The course Basics of 3D image processing:Acquisition and processing of 3D data is dedicated to technical approaches for the acquisition of depth information, the necessary data processing aspects. The focus is on optical approaches for 3D data acquisition, the corresponding system-technical realizations, the necessary theoretical basics as well as methods / procedures of (image) data processing.
Possible application areas of these techniques are nowadays very diverse and widespread, e.g. Computer graphics modelling of three-dimensional objects (reverse engineering), distance measurements in self-driving vehicles or for driver assistance, surface inspections or tests for dimensional accuracy in quality assurance, position estimates or obstacle localization in robotics or safety engineering. Methods for shape reconstruction contain elements and techniques of classical image processing to a large extent. In the same way, 3D aspects have to be increasingly taken into account nowadays to fulfill recognition tasks with monocular image processing.
The processing aspects for obtaining 3D information will be discussed in the lecture in an approach-oriented manner. The detailed presentation of the classical method of stereo and multi-camera vision is complemented by current approaches such as white-light interferometry, focus variation or the time-of-flight principle. The basic part of the course includes important system-technical, optical and geometrical laws of image acquisition processes as well as basic principles of projective geometry.
The student receives a comprehensive overview of procedures for the reconstruction of object surfaces up to the qualitative analysis of selected scene/object points in three-dimensional scenes. In addition, the theoretical foundations, the system-technical aspects and the methods / procedures for deriving spatial, geometric scene information from digital images are discussed.
Based on the imparted contents the student is able to use his knowledge in concrete applications in one of the above mentioned fields or can use it in the context of further lectures on applied image processing, e.g.
as well as on image-based pattern recognition / artificial intelligence.
The course is accompanied by exercises and excursions in which lecture content is reviewed and discussed in depth.
Historical and perceptual-physiological aspects of 3D acquisition
Overview of basic technical approaches to optical 3D acquisition
Algebraic description of geometric transformations, mappings and measurement arrangements
Binocular / multi-ocular incoherent optical approach to 3D acquisition
Primary data processing
Tsai modeling of measurement cameras
Polynocular measurement arrangements and system calibration
3D image processing
Solving the correspondence problem: Constraints and algorithms
Methods for subpixel accurate detection of structure locations
Pattern projection and structured light
3D over monocularly detected depth features / 3D aspects of image processing
Depth from -Motion, -Shading, -Texture, -Focus: principles and constraints of practical application
Further approaches to 3D acquisition relevant to practice
R. Hartley, A. Zisserman: Multiple View Geometry in computer vision. Cambridge University Press, 2010, ISBN 987-0-521-54051-3
G. Hauske, Systemtheorie der visuellen Wahrnehmung. Shaker Verlag 2003, ISBN 978-3832212933
R. Klette, A. Koschan, K. Schlüns: Computer Vision – Räumliche Information aus digitalen Bildern. Vieweg Verlag, Braunschweig/Wiesbaden, 1996, ISBN 3-528-06625-3
W. Richter: Grundlagen der Technischen Optik, Vorlesungsskripte, Technische Universität Ilmenau, Institut für Lichttechnik und Technische Optik, Fachgebiet Technische Optik
O. Schreer: Stereoanalyse und Bildsynthese, Springer, 2005, ISBN 3-540-23439-X
R. Szeliski: Computer Vision: Algorithms and Applications (Texts in Computer Science), Springer, 2nd ed. 2022 Auflage, ISBN: 978-3030343712, online: https://szeliski.org /Book
Th. Luhmann: Nahbereichsphotogrammetrie– Grundlagen, Methoden, Anwendungen. Wichmann Verlag, 2010
D. Kühlke: Optik – Grundlagen und Anwendung. Deutsch, Harri, Verlag GmbH, 2007
M. Kaschke et.al.: Optical Devices in OphthalmologyandOptometry: Technology, Design Principlesand Clinical Applications. Wiley-VCH, 2014
H. Gross: Handbook of Optical Systems. Vol.1; Vol.5, Wiley-VCH, 2005
Middlebury Stereo Vision Page:Taxonomy and comparison of many two-frame stereo correspondence algorithms.http://vision.middlebury.edu/stereo/
as well as the lecture notes for the subjects Systems Engineering and Systems Theory of Image Processing, Basics of Image Processing and Pattern Recognition (Image Processing 1) and Basics of Color Image Processing (Image Processing 2).
Completion by written examination, 60 min or oral examination (by arrangement).