Konrad Schindler: Catalogue data in Spring Semester 2020 |
| Name | Prof. Dr. Konrad Schindler |
| Field | Photogrammetry |
| Address | I. f. Geodäsie u. Photogrammetrie ETH Zürich, HIL D 42.3 Stefano-Franscini-Platz 5 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 30 04 |
| schindler@ethz.ch | |
| URL | https://igp.ethz.ch/personen/person-detail.html?persid=143986 |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 103-0254-AAL | Photogrammetry 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. | 6 credits | 13R | K. Schindler | |
| Abstract | The class conveys the basics of photogrammetry. It shall equip students with basic knowledge of the principles, methods and applications of image-based measurement. | ||||
| Learning objective | Understanding 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. | ||||
| Content | Fundamental concepts 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 3D reconstruction and stereoscopy; digital photogrammetric workstations; recording geometry and flight planning | ||||
| Lecture notes | Photogrammetry - Basics (slides on the web) Exercise material (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 / Notice | Requirements: knowledge of physics, linear algebra and analytical geometry, calculus, least-squares adjustment and statistics, basic programming skills. | ||||
| 103-0265-00L | Photogrammetry II  | 2 credits | 2G | K. Schindler, E. Baltsavias | |
| Abstract | This course covers advanced topics of aerial photogrammetry not treated in the basic course "Photogrammetrie". | ||||
| Learning objective | Understanding and application of the complete photogrammetric processing chain from flight planning through to orthophoto generation and 3D object reconstruction. | ||||
| Content | Aufbauend auf der Lehrveranstaltung "Photogrammetrie" werden in der Vorlesung die noch fehlenden Inhalte fuer das volle Verstaendnis der Luftbildphotogrammetrie vermittelt, insbesondere, die Buendelausgleichung, digitale Gelaendemodellierung und Laser-scanning. | ||||
| Literature | Vorgeschlagene Textbuecher: - Wolfgang Foerstner and Bernahrd Wrobel: Photogrammetric Computer Vision, Springer, 2016 - Thomas Luhmann: Nahbereichsphotogrammetrie. Grundlagen, Methoden, Beispiele, Wichmann Verlag, 4. Auflage 2018 - Richard Hartley and Andrew Zisserman: Multiple View Geometry, Cambridge University Press; 2. Auflage 2004 | ||||
| Prerequisites / Notice | Voraussetzung fuer den Kurs ist die Grundlagenvorlesungen "Photogrammetrie", oder ein aequivalenter Kurs an anderen Departmenten oder Universitaeten. Studierende, die keinen entsprechenden Kurs besucht haben, kontaktieren bitte unbedingt die Dozierenden, bevor sie sich anmelden. | ||||
| 103-0798-00L | Geodetic Project Course  Does not take place this semester. Number of participants limited to 24. | 5 credits | 9P | M. Rothacher, K. Schindler, A. Wieser | |
| Abstract | Field course with practical geodetic projects (3 weeks) | ||||
| Learning objective | Field course with practical geodetic projects (3 weeks) | ||||
| Content | Single-handed treatment of current geodetic projects in groups of 3-5 students. Writing of a technical report with description of the project, calculations, results and interpretations. Possibility to continue the work in a semester or diploma thesis. | ||||
| Prerequisites / Notice | The 3-weeks course takes place June 10-28. The first two weeks are dedicated to field work, the 3rd week to finalise the projects in Zurich. | ||||
| 103-0848-00L | Industrial Metrology and Machine Vision Number of participants limited to 30. | 4 credits | 3G | K. Schindler, A. Wieser | |
| Abstract | This course introduces contact and non-contact techniques for 3D coordinate, shape and motion determination as used for 3D inspection, dimensional control, reverse engineering, motion capture and similar industrial applications. | ||||
| Learning objective | Understanding the physical basis of photographic sensors and imaging; familiarization with a broader view of image-based 3D geometry estimation beyond the classical photogrammetric approach; understanding the concepts of measurement traceability and uncertainty; acquiring an overview of general 3D image metrology including contact and non-contact techniques (coordinate measurement machines; optical tooling; laser-based high-precision instruments). | ||||
| Content | CCD and CMOS technology; structured light and active stereo; shading models, shape from shading and photometric stereo; shape from focus; laser interferometry, laser tracker, laser radar; contact and non-contact coordinate measurement machines; optical tooling; measurement traceability, measurement uncertainty, calibration of measurement systems; 3d surface representations; case studies. | ||||
| Lecture notes | Lecture slides and further literature will be made available on the course webpage. | ||||
| 103-0849-00L | Multivariate Statistics and Machine Learning Number of participants limited to 40. | 4 credits | 4G | K. Schindler | |
| Abstract | Introduction to statistical modelling and machine learning. | ||||
| Learning objective | The goal is to familiarise students with the principles and tools of machine learning, and to enable them to apply them for practical data analysis. | ||||
| Content | multivariate probability distributions; comparison of distributions; regression; classification; model selection and cross-validation; clustering and density estimation; mixture models; neural networks | ||||
| Literature | C. Bishop: Pattern Recognition and Machine Learning, Springer 2006 T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning, Springer 2017 R. Duda, P. Hart, D. Stork: Pattern Classification, Wiley 2000 | ||||
| 103-0851-00L | Photogrammetry | 6 credits | 4G | K. Schindler | |
| Abstract | The class conveys the basics of photogrammetry. | ||||
| Learning objective | The aim is to equip students with an in-depth understanding of the principles, methods and applications of image-based 3D measurement. | ||||
| Content | 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 Triangulation and surface reconstruction; bundle adjustment; recording geometry and flight planning; airborne laser-scanning | ||||
| Literature | - Wolfgang Foerstner and Bernahrd Wrobel: Photogrammetric Computer Vision, Springer, 2016 - Thomas Luhmann, Stuart Robson, Stephen Kyle, Jan Boehm: Close-Range Photogrammetry and 3D Imaging, De Gruyter, 3rd edition 2019 - Richard Hartley and Andrew Zisserman: Multiple View Geometry, Cambridge University Press; 2nd edition 2004 | ||||