Lecture batch (2 Lectures), Date: 2nd May2020
3. Image acquisition, Camera geometry
11:00-11:45 EEST and repeated 20:00-20:45 EEST
4. Stereo and Multiview imaging
11:45-12:30 EEST and repeated 20:45-21:30 EEST
LECTURE DESCRIPTION
LECTURE 3: Image acquisition, Camera geometry
Saturday 2/5/2020, 11:00-11:45 EEST and repeated 20:00-20:45 EEST
Summary: After a brief introduction to image acquisition and light reflection, the building blocks of modern cameras will be surveyed, along with geometric camera modeling. Several camera models, like the pinhole and the weak-perspective camera model, will subsequently be presented. Projective geometry will be overviewed. with the most commonly used camera calibration techniques closing the lecture.
Sample lecture material
– sample slides DOWNLOAD
Related Literature:
- I. Pitas, “Computer vision”, Createspace/Amazon, in press.
- I. Pitas, “Digital video processing and analysis ” , China Machine Press, 2017 (in Chinese).
- I. Pitas, “Digital Video and Television ” , Createspace/Amazon, 2013.
- I. Pitas, Digital Image Processing Algorithms and Applications, J. Wiley, 2000.
- R. Szelinski, Computer Vision, Springer 2011
- Hartley R, Zisserman A. Multiple view geometry in computer vision. Cambridge university press; 2003.
- Davies, E. Roy. Computer vision: principles, algorithms, applications, learning. Academic Press, 2017
Lecture 4: Stereo and Multiview imaging
Saturday 2/5/2020, 11:45-12:30 EEST and repeated 20:45-21:30 EEST
Summary: Stereoscopic and multiview imaging will be explored in depth. The fundamentals of stereopsis will be overviewed. Stereoscopic vision, geometry will be presented, focusing on epipolar geometry, fundamental/essential matrix and camera rectification. Stereo camera technologies will be overviewed. Subsequently, the main methods of 3D scene reconstruction from stereoscopic video will be described based on feature detection and matching. Classical and neural disparity estimation methods will be presented. 3D depth estimation in parallel, converging and arbitrary camera geometries will be also presented, along with the basics of multiview imaging.
Sample lecture material
– sample slides DOWNLOAD
Related Literature
- I. Pitas, “Computer vision”, Createspace/Amazon, in press.
- R.Szelinski, “ Computer Vision ” , Springer 2011
- Hartley R, Zisserman A. , “ Multiple view geometry in computer vision” . Cambridge university press; 2003.
- Davies, E. Roy. “Computer vision: principles, algorithms, applications, learning ”. Academic Press, 2017
- Zbontar, Jure, and Yann LeCun. «Computing the stereo matching cost with a convolutional neural network.» Proceedings of the IEEE conference on computer vision and pattern recognition. 2015.
LECTURER
Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki, Greece. Since 1994, he has been a Professor at the Department of Informatics of the same University. He served as a Visiting Professor at several Universities.
His current interests are in the areas of image/video processing, machine learning, computer vision, intelligent digital media, human centered interfaces, affective computing, 3D imaging and biomedical imaging. He has published over 1138 papers, contributed in 50 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 70 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 42 such projects. He has 30000+ citations to his work and h-index 81+ (Google Scholar).
Prof. Pitas leads the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/. He is chair of the Autonomous Systems initiative https://ieeeasi.signalprocessingsociety.org.
Relevant links:
http://https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=en