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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.

Tutorial proposals are accepted until:

November 24, 2017

If you wish to propose a new Tutorial please kindly fill out and submit this Expression of Interest form.


Visual Intelligence in Egocentric (First-Person) Vision Systems  (VISIGRAPP)
Lecturer(s): Giovanni Maria Farinella

Visual Intelligence in Egocentric (First-Person) Vision Systems


Giovanni Maria Farinella
Università di Catania
Brief Bio
Giovanni Maria Farinella received the M.S. degree in Computer Science (egregia cum laude) from the University of Catania, Italy, in 2004, and the Ph.D. degree in computer science in 2008. He joined the Image Processing Laboratory (IPLAB) at the Department of Mathematics and Computer Science, University of Catania, in 2008. His research interests lie in the fields of computer vision, pattern recognition and machine learning. He has edited five volumes and coauthored more than 100 papers in international journals, conference proceedings and book chapters. He is a co-inventor of five international patents. He serves as a reviewer and on the programme committee for major international journals and international conferences. He founded (in 2006) and currently directs the International Computer Vision Summer School (ICVSS). More information:

Egocentric (First-Person) Vision paradigm allows to seamlessly acquire images of the world from the perspective of the agent (person, robot, etc) moving in an environment. Given their intrinsic mobility and the ability to acquire agent-related information, those systems have to deal with a continuously evolving environment. The challenge is to provide these systems an effective and robust Visual Intelligence. This tutorial will give an overview of the advances in the field. Challenges, applications and algorithms will be discussed by considering the past and recent literature.


Visual Intelligence, Egocentric Vision, First Person Vision, Wearable Vision

Target Audience

This course is intended for those with a general computing background, and with interest in the topic of image processing, computer vision and machine learning. Ph. D. students, post-docs, young researchers (both academic and industrial), senior researchers (both academic and industrial) or academic/industrial professionals will benefit from the general overview and the introduction of the most recent advances of the field.

Detailed Outline

- Introduction and Motivation

- Open Challenges

- State-of-the-Art Algorithms

- Applications and Opportunities

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