Dear Computer Vision/Machine Learning/Autonomous Systems students, engineers, scientists and enthusiasts,

Artificial Intelligence and Information analysis (AIIA) Lab, Aristotle University of Thessaloniki, Greece is proud to launch the live CVML Web lecture series that will cover very important topics Computer vision/machine learning. Two lectures will take place on Saturday 2nd May 2020:

1) Image acquisition, Camera geometry

2) Stereo and Multiview imaging

Date/time:

a) Saturday 11:00-12:30 EET (17:00-18:30 Beijing time) for audience in Asia and

b) Saturday 20:00-21:30 EET (13:00-14:30 EST, 10:00-11:30 PST for NY/LA, respectively) for audience in the Americas.

Registration can be done using the link: http://icarus.csd.auth.gr/cvml-web-lecture-series/

Lectures abstract

1) Image acquisition, Camera geometry

Abstract: 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.

2) Stereo and Multiview imaging

Abstract: 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.

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 lead the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/ and is principal investigator (AUTH) in H2020 projects Aerial Core and AI4Media. He is chair of the Autonomous Systems initiative https://ieeeasi.signalprocessingsociety.org/.

Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el

AIIA Lab www.aiia.csd.auth.gr

Lectures will consist primarily of live lecture streaming and PPT slides. Attendees (registrants) need no special computer equipment for attending the lecture. They will receive the lecture PDF before each lecture and will have the ability to ask questions real-time. Audience should have basic University-level undergraduate knowledge of any science or engineering department (calculus, probabilities, programming, that are typical e.g., in any ECE, CS, EE undergraduate program). More advanced knowledge (signals and systems, optimization theory, machine learning) is very helpful but nor required.

These two lectures are part of a 14 lecture CVML web course ‘Computer vision and machine learning for autonomous systems’ (April-June 2020):

Introduction to autonomous systems (delivered 25th April 2020)

Introduction to computer vision (delivered 25th April 2020)

Image acquisition, camera geometry (scheduled 2nd May 2020)

Stereo and Multiview imaging (scheduled 2nd May 2020)

3D object/building/monument reconstruction and modeling

Signals and systems. 2D convolution/correlation

Motion estimation

Introduction to Machine Learning

Introduction to neural networks, Perceptron, backpropagation

Deep neural networks, Convolutional NNs

Deep learning for object/target detection

Object tracking

Localization and mapping

Fast convolution algorithms. CVML programming tools.

Sincerely yours

Prof. Ioannis Pitas

Director of AIIA Lab, Aristotle University of Thessaloniki, Greece