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The role of the tutorials is to provide a platform for a more intensive scientific exchange amongst researchers interested in a particular topic and as a meeting point for the community. Tutorials complement the depth-oriented technical sessions by providing participants with broad overviews of emerging fields. A tutorial can be scheduled for 1.5 or 3 hours.


Ontologies for Intelligent Vision Systems  (KEOD)
Instructor : Joanna Isabelle Olszewska

Ontologies for Intelligent Vision Systems


Joanna Isabelle Olszewska
University of the West of Scotland
United Kingdom
Brief Bio
Joanna Isabelle Olszewska is a British Computer Scientist. She is an Assistant Professor (Lecturer) with UWS, UK, and leads research in Algorithms and Softwares for Intelligent Vision Systems. She is a member of the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems. She is an ACM Distinguished Speaker and has given talks, e.g. at the University of Cambridge, at conferences such as ICRA, and at events such as EPSRC/BMVA Technical Days and DDD Scotland, ACM Future Worlds as well as interviews, e.g. for the BBC Lunch Time 'Women in Engineering' Program. She has been TPC member of over 70 international conferences such as IJCAI and chaired over 60 conference/workshop sessions, e.g. at IROS.

Intelligent Vision Systems are increasingly present in our Society from street surveillance cameras to indoor sport training set-ups, from drones to companion robots. To ensure an efficient communication between these systems and operating agents, ontologies provide an effective and interoperable solution well suited for real-world interactions. Thus, this tutorial introduces the topic of ontologies for intelligent vision systems in light of the main challenges in that research field and the developed solutions and standards based on computer vision and artificial intelligence methods.


Domain Ontologies, Domain Analysis and Modeling, Knowledge Representation, Knowledge Engineering¸ Spatio-Temporal Visual Ontology, Integration and Interoperability, Human-Machine Cooperation, Decision Support Systems, Intelligent Vision Systems

Aims and Learning Objectives

This tutorial aims to present the ‘why’ and ‘how’ of the ontologies for intelligent vision systems deployed in constrained and unconstrained environments.

Participants are expected to acquire new perspectives about intelligent vision systems’ challenges and their related ontological solutions. In more detail, the objectives of this tutorial are:
I) To appreciate intelligent vision systems’ challenges;
II) To understand the corresponding ontological solutions for the intelligent vision systems;
III) To get new trends and future directions of the Ontologies for Intelligent Vision Systems research and standards.

Target Audience

This tutorial is intended for a broad spectrum of participants both from academia and industry.

Prerequisite Knowledge of Audience


Detailed Outline

The tentative list of the topics covered by this tutorial is:
a) Ontology Domain: Intelligent Vision Systems
b) Knowledge Representation of Intelligent Vision Systems
c) Spatio-Temporal Visual Ontology (STVO)
d) Integration, Interoperability & Related Ontological Standards

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