Jan Dirk Wegner: Catalogue data in Autumn Semester 2017 |
| Name | Prof. Dr. Jan Dirk Wegner (Professor Universität Zürich (UZH)) |
| Address | I. f. Geodäsie u. Photogrammetrie ETH Zürich, HIL D 44.2 Stefano-Franscini-Platz 5 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 68 08 |
| jan.wegner@geod.baug.ethz.ch | |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 103-0267-01L | Photogrammetry and 3D Vision Lab  Prerequisites: It is suggested that students take the course "Photogrammetrie" at bachelor level before this one. | 3 credits | 2G | J. D. Wegner | |
| Abstract | The course deals with selected topics of close-range photogrammetry and geometric computer vision, including wide-baseline image matching and reconstruction, dense surface reconstruction, image search and indexing; emphasis is put on reading and self-study and on practical project work, typically in groups. | ||||
| Objective | The aim of the course is to get to know the methods and practice of close-range photogrammetric reconstruction, and an in-depth understanding of selected topics in modern close-range photogrammetry and computer vision. | ||||
| Content | This course builds in part on the courses "Photogrammetrie", "Bildverarbeitung" and "Photogrammetrie II" from the Bachelor program. It focusses on the particular challenges of automated close-range photogrammetry. | ||||
| Lecture notes | Presentation slides, necessary publications and complementary learning materials will be provided through a dedicated course web-site. | ||||
| Literature | Recommended textbooks: - T. Luhmann. Nahbereichsphotogrammetrie (also available in English ) - R. Hartley and A. Zisserman. Multi-view geometry in computer vision - R. Szeliski. Computer Vision | ||||
| Prerequisites / Notice | A recommended prerequisite for taking this course are the Bachelor courses "Photogrammetrie", "Bildverarbeitung" and "Photogrammetrie II". If you have not passed them, please contact the main lecturer of the course before enrolling. The course will include both practical work with commercial software, and programming in Matlab. | ||||
| 103-0274-AAL | Image Processing Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 3 credits | 2R | J. D. Wegner | |
| Abstract | The objective of this lecture is to introduce the basic concepts of image formation and explain the basic methods of signal and image processing. | ||||
| Objective | Understanding core methods and algorithms in image processing and computer vision and the underlying signal processing foundations. Applying image processing algorithms to relevant problems in photogrammetry and remote sensing. | ||||
| Content | - Image segmentation The following topics will be covered in the course: - Properties of digital images - Signal processing/Sampling - Image enhancement - Image restoration: Spatial domain - Image restoration: Fourier domain - Color/Demosaicing - Image compression - Feature extraction - Texture analysis | ||||
| Lecture notes | A script will be provided as PDF files on the lecture website. | ||||
| Literature | We suggest the following textbooks for further reading: Rafael C. Gonzalez, Richard E. Woods Digital Image Processing Prentice Hall International, 2008 ISBN: 013168728X Rafael C. Gonzalez, Steven L. Eddins, Richard E. Woods: Digital Image Processing Using MATLAB Prentice Hall, 2003 ISBN: 0130085197 | ||||
| Prerequisites / Notice | The course is accompanied by programming assignments, that need to be completed in order to pass the semester performance. | ||||