Konrad Schindler: Catalogue data in Autumn Semester 2018

Name Prof. Dr. Konrad Schindler
I. f. Geodäsie u. Photogrammetrie
ETH Zürich, HIL D 42.3
Stefano-Franscini-Platz 5
8093 Zürich
Telephone+41 44 633 30 04
DepartmentCivil, Environmental and Geomatic Engineering
RelationshipFull Professor

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.
5 credits4RK. Schindler
AbstractThe class conveys the basics of photogrammetry. Its aim is to equip students with an understanding of the principles, methods and applications of image-based measurement.
ObjectiveThe aim is an understanding of the principles, methods and possible applications of photogrammetry. The course also forms the basis for more in-depth studies and self-reliant photogrammetric project work in further photogrammetry courses.
ContentThe basics of photogrammetry, its products and applications: the principle of image-based measurement; digital aerial cameras and related sensors; projective geometry; mathematical modeling, calibration and orientation of cameras; photogrammetric reconstruction of points and lines, and stereoscopy; orthophoto generation; digital photogrammetric workstations; recording geometry and flight planning
Lecture notesPhotogrammetry (slides on the web)
Literature- Kraus, K.: Photogrammetrie, Band 1: Geometrische Informationen aus Photographien und Laserscanneraufnahmen, mit Beiträgen von Peter Waldhäusl, Walter de Gruyter Verlag, Berlin, 7th edition
- Kraus, K.: Photogrammetrie, Band 2: Verfeinerte Methoden und Anwendungen, mit Beiträgen von J. Jansa und H. Kager, Walter de Gruyter Verlag, Berlin, 3rd edition
- Thomas Luhmann: Nahbereichsphotogrammetrie. Grundlagen, Methoden und Anwendungen, H. Wichmann Verlag, Karlsruhe, 2nd edition 2003
- Richard Hartley and Andrew Zisserman: Multiple View Geometry, Cambridge University Press; 2nd edition 2004
Prerequisites / NoticeRequirements: knowledge of physics, linear algebra and analytical geometry, calculus, least-squares adjustment and statistics, basic programming skills.
103-0287-00LImage Interpretation4 credits3GK. Schindler
AbstractIntroduction to interactive, semi-automatic and automatic methods for image interpretation and data analysis; methodological aspects of computer-assisted remote sensing, including semantic image classification and segmentation; detection and extraction of individual objects; estimation of physical parameters.
ObjectiveUnderstanding the tasks, problems, and applications of image interpretation; basic introduction of computational methods for image-based classification and parameter estimation (clustering, classification, regression), with focus on remote sensing.
ContentImage (and point-cloud) interpretation tasks: semantic classification (e.g. land-cover mapping), physical parameter estimation (e.g. forest biomass), object extraction (e.g. roads, buildings);
Image coding and features; probabilistic inference, generative and discriminative models; clustering and segmentation; continuous parameter estimation, regression; classification and labeling; deep learning; atmospheric influences in satellite remote sensing;
LiteratureJ. A. Richards: Remote Sensing Digital Image Analysis - An Introduction
C. Bishop: Pattern Recognition and Machine Learning
Prerequisites / Noticebasics of probability theory and statistics; basics of image processing; elementary programming skills (Matlab);
103-0817-00LGeomatics Seminar Restricted registration - show details 4 credits2SM. Rothacher, K. W. Axhausen, A. Geiger, A. Grêt-Regamey, L. Hurni, M. Raubal, K. Schindler, A. Wieser
AbstractIntroduction to general scientific working methods and skills in the core fields of geomatics. It includes a literature study, a review of one of the articles, a presentation and a report about the literature study.
ObjectiveLearn how to search for literature, how to write a scientific report, how to present scientific results, and how to critically read and review a scientific article
ContentA list of themes for the literature study are made availabel at the beginning of the semester. A theme can be selected based on a moodle.
Prerequisites / NoticeAgreement with one of the responsible Professors is necessary