Presentation abstract
This talk will explore recent advances in video-based human activity recognition aimed at creating adaptable, resource-efficient, and uncertainty-aware models for assisting humans in everyday situations. Topics covered will include: (1) an overview state-of-the-art methods and public datasets for human activity recognition in different assistive scenarios (2) the importance of adaptability in human observation systems to cater to new situations (environments, appearances, behaviours) as well as strategies for addressing such open world tasks, and (3) incorporating uncertainty-aware approaches, vital for robust and safe decision-making. The talk will conclude with a discussion of future research directions and the potential applications of these models, such as technology for elderly assistance or medical diagnostics.
Presenter
Alina Roitberg is a Tenure-Track Juniorprofessor at the University of Stuttgart, leading the newly established Intelligent Sensing and Perception Group at the Institute for AI, University of Stuttgart. She is also a Faculty member of the International Max Planck Research School for Intelligent Systems (IMPRS-IS). Before joining the University of Stuttgart, she was a postdoctoral researcher at KIT and a Visiting Researcher at Johannes Kepler University Linz.
She received her PhD from KIT in 2021, during which she completed a research internship at Facebook Zurich. For her doctoral work, she was recognized with multiple awards, including the IEEE ITSS Best Dissertation Award and the Helmholtz Doctoral Prize. Her research interests include computer vision, human activity recognition, domain adaptation, open set recognition, as well as resource- and data-efficient learning.