March 27, 2020: Invited Speaker Seminar: Deep Learning and Drone Vision for Infrastructure Inspection

Dr. Ioannis Pitas
Aristotle University of Thessaloniki

Friday, March 27, 2020 at 11:00 am
Room EV002.260

Abstract

Drone vision plays a pivotal role in drone perception/control, because it: a) enhances flight safety by drone localization/mapping, obstacle detection and emergency landing detection; b) performs quality visual data acquisition, particularly as related to inspection accuracy and c) allows powerful drone/human interactions, e.g., through automatic event detection, gesture control, person/crowd avoidance. The use of multiple drones (drone swarms) is an important new trend in several application areas, as it enables: a) drone mission speedup by task distribution to drones (e.g., for terrain/infrastructure surveillance), b) simultaneous information acquisition (e.g., multi-view shooting of an event), c) support of heterogenous drones (e.g., multicopter and fixed wing ones). Such systems should be able to survey/inspect big areas over large expanses, ranging, for example, from a building to a highway or an electric power line. The drone should have: a) increased drone decisional autonomy, hence allowing mission time of at least one hour in an outdoor environment (possibly through drone swapping), b) improved drone robustness and safety mechanisms (e.g., communication robustness/safety, embedded flight regulation compliance, enhanced emergency landing mechanisms), c) special perching and landing mechanisms, d) allow human-coworking for safe infrastructure maintenance. Such robustness is particularly important, if the drones will operate close to sensitive infrastructure (e.g., electric power lines) and/or may face environmental hazards (e.g., wind, dust). Therefore, it must be contextually aware and adaptive. Drone vision and machine learning play a very important role towards this end, covering the following topics: a) semantic world mapping, b) drone and multiple target localization, c) 2D/3D target tracking, d) detection/localization of special objects (e.g., long power lines, material, tools), e) drone visual analysis for target/obstacle/object-of-interest detection, f) support of heterogeneous sensors (e.g., video/IR cameras, LIDAR), and g) understanding human status towards co-working with them. Finally, embedded on-drone vision (e.g., tracking) and machine learning algorithms are extremely important, as they facilitate drone autonomy, e.g., in communication-denied environments.

The lecture will offer an overview of all the above plus other related topics, stressing the algorithmic aspects, such as: a) drone localization and world mapping, b) multiview object detection, tracking and 3D localization, c) deep human activity recognition and d) embedded CNN and fast convolution computing.

Biography

Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received a 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 interfaces, affective computing, 3D imaging and biomedical imaging. He has published over 906 papers, contributed in 47 books in his areas of interest and edited or (co-)authored another 11 books. He has also been a 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 a principal investigator/researcher in 42 such projects. He has 30600+ citations to his work and h-index 82+ (Google Scholar). Prof. Pitas leads the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/. He is chair of the Autonomous Systems initiative http://asi.politecnica.unige.it/.