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Perception and Activity Understanding
The research group on the understanding of perception and activity conducts research analyses of human activities from multimodal data. This includes investigating the fundamental tasks of scene analysis such as detection, segmentation and tracking of people, their representation, and the characterization of their condition, as well as the modeling of sequential data and their interpretation in the form of gestures, activities, behavior, or social relationships, through the design of sound algorithms which exploit and extend models and methods of computer vision, machine learning, and multimodal data-fusion. Surveillance, traffic analysis, analysis of behavior, human-robot interfaces, and multimedia content analysis are the main application domains.
Current Group Members
The Perception and Activity Understanding group has an opening in computer vision and machine learning.
The Eumssi team led by Idiap and comprising as well the LIUM partner ranked first out of 6 teams in the Person Discovery challenge of the MediaEval benchmarking initiative.