<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">
<div>Dear all,</div>
<div><br>
</div>
<div>University of Udine (Udine, Italy) and University of Catania (Catania, Italy) are seeking very motivated candidates in view of the opening of research fellow positions to work on the TEAM project, “Tracking in Egovision for Applied Memory” funded by the
Italian Ministry of University and Research (MUR) through the PRIN 2022 PNRR program. Our common goal is to build an artificial memory of human-object interactions supported by first person vision-based object tracking algorithms. The purpose of this Call
for Expression of Interest is to identify the potential candidates that would be interested to join our team as research fellows.</div>
<div><br>
</div>
<div><br>
</div>
<div><b>Project Overview:</b></div>
<div><br>
</div>
<div>Computer vision algorithms for wearable devices like smart glasses and AR headsets can offer user-centric experiences by understanding the user's surroundings and aiding in tasks. Current methods typically focus on understanding short-term, category-level
object interactions from a static perspective, whereas humans have long-range, instance-based, and opportunistic interactions with objects. To emulate the way of human understanding, the TEAM project aims to develop a computer vision system able to 1) discover
important objects to be tracked and highlight their relationships with other objects, 2) track the discovered objects in an instance-based long-term fashion, 3) use information about the detected objects and associated object tracks to form symbolic, high-level
and compact memories describing past user interactions, 4) exploit such memories to carry out downstream tasks. This system will comprise an object interaction discovery module, a long-term visual object tracking module, and a memory formation module. The
goal is to create technology for long-term user-object interaction understanding, particularly valuable in healthcare for cognitive assessment and training using wearable cameras.</div>
<div><br>
</div>
<div>More information on the project can be found at our web page: https://sites.google.com/view/prin-pnrr-team/</div>
<div><br>
</div>
<div><br>
</div>
<div><b>Position Requirements:</b></div>
<div><br>
</div>
<div>• A Master's Degree title (PhD preferred).</div>
<div>• A strong background in Computer Vision or related fields.</div>
<div>• Familiarity with object tracking, egocentric vision, and behavioural analysis.</div>
<div>• Ability to work collaboratively within a multi-disciplinary team.</div>
<div><br>
</div>
<div>Interested candidates are encouraged to submit an expression of interest through this application form: https://forms.office.com/e/tccG7V85sb</div>
<div><br>
</div>
<div><br>
</div>
<div>Christian Micheloni, University of Udine</div>
<div>Antonino Furnari, University of Catania</div>
</body>
</html>