The course will take place as live web course.

DESCRIPTION

Our dream to make autonomous machines sense and perceive (notably see) comes true: Nowadays Computer Vision enables diverse applications:

  • Autonomous Systems (cars, drones, vessels) Perception,
  • Robotics Perception and Control.

The same computer vision technologies can power other important application areas:

  • Intelligent Human-Machine Interaction,
  • Anthropocentric (human-centered) Computing,
  • Smart Cities/Buildings and Assisted living.

This two-day short course focuses on Autonomous Systems vision, perception and imaging, while providing an overview and in-depth presentation of the various computer vision and deep learning problems encountered in autonomous systems perception. It consists of two parts (A, B) and each of them including 8 one-hour lectures and related material (slide pdfs, lecture videos, understanding questionnaires).

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.

UNIVERSITY AUTH

This short course is hosted by Aristotle University of Thessaloniki (AUTH). It is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews and is the biggest University in SE Europe.

WHEN?

The course will take place as a live web course on 5-6 May 2021.

PROGRAM

You can click on the lecture title to view its description.

Time*/date 5/05/2021 6/05/2021
08:00 – 08:30 Registration  
09:00 – 10:00 Digital images and videos Autonomous Systems Sensors
10:00 – 11:00 Image Acquisition. Camera Geometry Deep object detection
11:00 – 11:30 Coffee break Coffee break
11:30 – 12:30 Stereo and Multiview Imaging Object Tracking
12:30 – 13:30 Structure from Motion Object Pose Estimation
13:30 – 14:30 Lunch break Lunch break
14:30 – 15:30 3D Robot Localization and Mapping Multiple Drone Systems
15:30 – 16:30 Neural 3D world modeling Autonomous Car Vision
16:30 – 17:00
Coffee break
Coffee break
17:00 – 18:00
Image/Point cloud registration Autonomous Surface Vessels
18:00 – 19:00
Deep semantic image segmentation CVML Software Development Tools

 

*Eastern European Time (EET)

**This programme is indicative and may be modified without prior notice by announcing (hopefully small) changes in lectures/lecturers.

***Each topic will include a 45-minute lecture and a 15-minute break.

 

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 (AUTH), Greece. Since 1994, he has been a Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab. He served as a Visiting Professor at several Universities.

His current interests are in the areas of computer vision, machine learning, autonomous systems, intelligent digital media, image/video processing, human-centred computing, affective computing, 3D imaging and biomedical imaging. He has published over 1000 papers, contributed in 47 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. Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/. He is AUTH principal investigator in H2020 R&D projects Aerial Core and AI4Media. He is chair of the Autonomous Systems Initiative https://ieeeasi.signalprocessingsociety.org/. 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+ (Google Scholar)

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

Professor Pitas will deliver 16 lectures on deep learning and computer vision.

Educational record of Prof. I. Pitas: He was Visiting/Adjunct/Honorary Professor/Researcher and lectured at several Universities: University of Toronto (Canada), University of British Columbia (Canada), EPFL (Switzerland), Chinese Academy of Sciences (China),  University of Bristol (UK), Tampere University of Technology (Finland), Yonsei University (Korea), Erlangen-Nurnberg University (Germany), National University of Malaysia, Henan University (China). He delivered 90 invited/keynote lectures in prestigious international Conferences and top Universities worldwide. He run 17 short courses and tutorials on Autonomous Systems, Computer Vision and Machine Learning, most of them in the past 3 years in many countries, e.g., USA, UK, Italy, Finland, Greece, Australia, N. Zealand, Korea, Taiwan, Sri Lanka, Bhutan.

https://aiia.csd.auth.gr/computer-vision-machine-learning/#pitas

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

 

REGISTRATION

Early registration (till 23/04/2021):

• Standard: 300 Euros

• Undergraduate/MSc/PhD student*: 200 Euros

Later or on-site registration (after 23/04/2021):

• Standard: 350 Euros

• Undergraduate/MSc/PhD student*: 250 Euros

*Proof of student status should be provided upon registration.

Register!!!

After the completion of your payment, please fill in the form below:

Complete your registration

Up to 10 PhD students, registered in AUTH or in any AI4Media or ELISE or Humane-AI-Net or VISION CSA or TAILOR University partners, are entitled for 1 free CVML Web Course registration per fall/spring semester on a FCFS basis, with priority to ones working on AI-related topics. This offer is related to the upcoming educational activities of International AI Doctoral Academy (AIDA) that is co-initiated by these two projects.

Please send email with tilte «Spring School 2021 – Computer Vision for Autonomous Systems: free registration» to koroniioanna@csd.auth.gr, if you belong to the above category.

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Lectures will be in English. PDF slides will be available to course attendees.

A certificate of attendance will be provided.

  • Certificate of attendance without ECTS: Upon successful completion of more than 14 lectures.
  • Certificate of attendance with ECTS: Upon successful completion of more than 14 lectures and successful answer to questionnaires (mark equal or above 5 in the range 0-10, 10 being excellent).

***The short course on «CVML Short Course – Computer Vision for Autonomous Systems» will take place as live web course on 5-6 May 2021. Lectures will be prerecorded to facilitate attendees in case they experience problems due to time difference. Remote participation will be available via teleconferencing.***

Cancelation policy:

  • 50% refund for cancelation up to 16/04/2021
  • 0% refund afterwards

_______________________________________________________________

KNOWLEDGE SELF-ASSESSMENT

You may want to self-assess your knowledge on Computer Vision and Image Processing topics, by trying the assessment exercises in  https://aiia.csd.auth.gr/cvml-knowledge-self-assessment/ before and after studying this course.

It takes you only 15 min per questionnaire. You can do this double self-assessment (before/after study) for free, using the sample lecture study material provided below.

CVML PROGRAMMING EXERCISES

Goal: Improve your programming knowledge on Computer Vision, Machine Learning and Image/Video Processing topics using OpenCV, PyTorch and CUDA and your skills on building, e.g.. Convolutional Neural Networks and applying object tracking methods.

https://aiia.csd.auth.gr/cvml-programming-exercises/

CVML SOFTWARE

The following tools are available for demos and student training in the various CVML courses:

  1. 2D computer vision and image processing software EIKONA.
  2. 3D image processing and analysis software EIKONA3D.

TOPICS

5th May 2021 – Part A: (first day, 8 lectures)
Computer Vision
Digital images and videos
Image Acquisition. Camera Geometry
Stereo and Multiview Imaging
Structure from Motion
3D Robot Localization and Mapping
Neural 3D world modeling
Image/Point cloud registration
Deep semantic image segmentation

6th May 2021 – Part B: (second day, 8 lectures)
Autonomous Systems
Autonomous Systems Sensors
Deep object detection
Object Tracking
Object Pose Estimation
Multiple Drone Systems
Autonomous Car Vision
Autonomous Surface Vessels
CVML Software Development Tools

AUDIENCE

Any engineer or scientist practicing or student having some knowledge of Signals and Systems, and Machine Learning, notable CS, CSE, ECE, EE students, graduates or industry professionals with relevant background.

IF I HAVE A QUESTION?

Contact

 

PAST COURSE EDITIONS

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Winter School 2021

Participants: 30

Countries: France, Spain, United States, Ireland, Poland, Sweden, Norway, Poland, Greece, Malta.

Registrants comments:

  • «The quality of the lectures was high; the professor did a very good job explaining clearly all the concepts. It went according to the plan, and to my personal expectations.»
  • «Personal experience is always important in this kind of courses. Sometimes adds more gain than general theory.»
  • «It was an intensive ride through a wide range of topics regarding drones in research, which I enjoyed quite a lot. It was helpful to brush on past knowledge and accumulate new one. The course also offered me the possibility to encounter a community of passionate researchers which can only motivate me to work harder.»

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Fall School 2020

Participants: 35

Countries: France, Taiwan, United States, Sweden, Denmark, Germany, Pittsburgh, Germany, Greece, England, Italy, Spain, Iceland.

Registrants comments:

  • «The quality of the lectures was high; the professor did a very good job explaining clearly all the concepts. It went according to the plan, and to my personal expectations.»
  • «Personal experience is always important in this kind of courses. Sometimes adds more gain than general theory.»
  • «It was an intensive ride through a wide range of topics regarding drones in research, which I enjoyed quite a lot. It was helpful to brush on past knowledge and accumulate new one. The course also offered me the possibility to encounter a community of passionate researchers which can only motivate me to work harder.»

——————————————————————————————————————

Summer School 2020 (held as a web course due to Covid-19 circumstances)

Countries: Belgium, Ireland, Greece, Finland, China, Italy, France, Croatia, Spain, United Kingdom

Registrants comments:

  • «Very interesting lecture topics regarding the autonomous systems perception.»
  • «The overall course was quite interesting and fulfilling in terms of the context promised.»
  • «The lectures were very appealing and satisfactorily delivered.»

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Summer School 2019

Participants: 39

Countries: United Kingdom, Scotland, Germany, Italy, Norway, Slovakia, Spain, Croatia, Czech Republic, Greece

Registrants comments: 

  • «Very adequate information about the topics of DL, CV and autonomous systems.»
  • «Very good coverage of autonomous systems vision perception.»
  • «Course’s content was greatly explanatory with many application examples.»
  • «Very well structured course, knowledgeable lecturers.»

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SAMPLE COURSE MATERIAL & RELATED LITERATURE

  1. Pitas, 3D imaging science and technologies, Amazon CreateSpace preprint, 2021.
  2. Pitas, Computer Vision and Machine Learning, Amazon CreateSpace preprint, 2021.
  3. Pitas, Digital video processing and analysis, China Machine Press, 2017 (in Chinese).
  4. Pitas, Graph analysis in social media, editor, CRC Press, 2016.
  5. Pitas, Digital Video and Television, Createspace/Amazon, 2013.
  6. Pitas, Digital Image Processing Algorithms and Applications, J. Wiley, 2000.
  7. Nikolaidis and I. Pitas, 3D Image Processing Algorithms, J. Wiley, 2000.

 

USEFUL LINKS

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

•Department of Computer Science, Aristotle University of Thessaloniki (AUTH): https://www.csd.auth.gr/en/

Laboratory of Artificial Intelligence and  Information Analysis: http://www.aiia.csd.auth.gr/

•Thessaloniki: https://wikitravel.org/en/Thessaloniki