[visionlist] Modified Date: Invitation to join 2021 Spring School 'CVML Short Course - Computer Vision for Autonomous Systems', 26-27th May 2021 (6th edition)
Ioanna Koroni
ioannakoroni at csd.auth.gr
Wed May 12 04:51:06 -04 2021
Dear Computer Vision, Deep Learning and/or Autonomous systems engineers,
scientists and enthusiasts,
you are welcomed to register in this CVML Short e-course on 'Computer Vision
for Autonomous Systems', 26-27th May 2021:
<https://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-aut
onomous-systems/>
https://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auto
nomous-systems/
It will take place as a two-day e-course (due to COVID-19 circumstances),
hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki,
Greece, providing a series of live lectures delivered through a
tele-education platform. They will be complemented with on-line video
recorded lectures and lecture pdfs, to facilitate international participants
having time difference issues and to enable you to study at own pace. You
can also self-assess your knowledge, by filling appropriate questionnaires
(one per lecture). You will be provided programming exercises to improve
your programming skills.
It is part of the very successful CVML short course series that took place
in the last three years.
The short e-course consists of 16 1-hour live lectures organized in two
Parts (1 Part per day):
Part A lectures (8 hours) provide an in-depth presentation of 2D and 3D
Computer Vision theory and applications in the above-mentioned diverse
domains, primarily for semantic 3D world modeling and localization. Computer
Vision starts with a detailed presentation of digital image/video
fundamentals and image acquisition and camera geometry, including camera
calibration. Then, two lectures on: a) Stereo and Multiview imaging and b)
Structure from motion will provide the theoretical and algorithmic tools to
recover 3D world models from images. They will be used on Localization and
mapping that is of primary importance in Autonomous Systems and Robotic
perception. This is complemented by Neural techniques for recovering depth
information and 3D world modeling, even from monocular images. Deep semantic
image segmentation will conclude this part, by providing DNN methods both to
label and segment regions, e.g., roads and targets, e.g., cars, pedestrians.
Part B lectures (8 hours) will start with an overview of Autonomous Systems
Sensors. Then , it will provide an in-depth presentation of Computer Vision
theory and applications in autonomous systems, particularly as related to
target detection, tracking and object pose estimation. Applications will be
presented for Multiple Drone Systems Autonomous Car Vision and Autonomous
Marine Surface Vessels. Finally, CVML programming tools (e.g., DNN
frameworks, BLAS/cuBLAS, DNN and CV libraries) are overviewed, as they allow
fast application of all the above knowledge in almost any application
domain.
Course lectures
Part A: Computer Vision (first day, 8 lectures)
1. Digital images and videos
2. Image Acquisition. Camera Geometry
3. Stereo and Multiview Imaging
4. Structure from Motion
5. 3D Robot Localization and Mapping
6. Neural 3D world modeling
7. Image/Point cloud registration
8. Deep semantic image segmentation
Part B: Autonomous Systems (second day, 8 lectures)
1. Autonomous Systems Sensors
2. Deep object detection
3. Object Tracking
4. Object Pose Estimation
5. Multiple Drone Systems
6. Autonomous Car Vision
7. Autonomous Surface Vessels
8. CVML Software Development Tools
Though independent, the attendees of this short e-course will greatly
benefit by attending the CVML Short e-course on 'Machine Learning and Deep
Neural Networks' 27-28th April 2021:
<http://icarus.csd.auth.gr/spring-cvml-short-course-machine-learning-and-dee
p-neural-networks/>
http://icarus.csd.auth.gr/spring-cvml-short-course-machine-learning-and-deep
-neural-networks/
You can use the following link for course registration:
<http://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auto
nomous-systems/>
http://icarus.csd.auth.gr/spring-cvml-short-course-computer-vision-for-auton
omous-systems/
Lecture topics, sample lecture ppts and videos, self-assessment
questionnaires and programming exercises can be found therein.
For questions, please contact: Ioanna Koroni <
<mailto:koroniioanna at csd.auth.gr> koroniioanna at csd.auth.gr>
The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow,
Chair of the IEEE SPS Autonomous Systems Initiative, Director of the
Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle
University of Thessaloniki, Greece, Coordinator of the European Horizon2020
R&D project Multidrone. He is ranked 249-top Computer Science and
Electronics scientist internationally by Guide2research (2018). He is head
of the EC funded AI doctoral school of Horizon2020 EU funded R&D project
AI4Media (1 of the 4 in Europe). He has 32200+ citations to his work and
h-index 85+.
AUTH is ranked 153/182 internationally in Computer Science/Engineering,
respectively, in USNews ranking.
Relevant links:
1) Prof. I. Pitas:
<https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el>
https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
2) Horizon2020 EU funded R&D project Aerial-Core: <https://aerial-core.eu/>
https://aerial-core.eu/
3) Horizon2020 EU funded R&D project Multidrone: <https://multidrone.eu/>
https://multidrone.eu/
4) Horizon2020 EU funded R&D project AI4Media: <https://ai4media.eu/>
https://ai4media.eu/
5) AIIA Lab: <https://aiia.csd.auth.gr/> https://aiia.csd.auth.gr/
Sincerely yours
Prof. I. Pitas
Director of the Artificial Intelligence and Information analysis Lab (AIIA
Lab)
Aristotle University of Thessaloniki, Greece
Post scriptum: To stay current on CVML matters, you may want to register in
the CVML email list, following instructions in:
<https://lists.auth.gr/sympa/info/cvml>
https://lists.auth.gr/sympa/info/cvml
--
This email has been checked for viruses by Avast antivirus software.
https://www.avast.com/antivirus
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20210512/1b30a7ea/attachment.html>
More information about the visionlist
mailing list