Grammars of Human Activity
Yiannis Aloiomonos
University of Maryland College Park

Abstract:

One of the major goals of Cognitive Systems is to interpret human
activity sensed by a variety of sensors. In order to develop useful
technologies and a subsequent industry around cognitive interaction
technology, we need to proceed in a principled manner. This talk
suggests that human activity can be expressed in a language. This is a
special language with its own phonemes, its own morphemes (words) and
its own syntax and it can be learned using machine learning techniques
applied to gargantuan amounts of data collected by sensor networks. I
will present two examples of grammatical frameworks that we have been
developing over the past few years and their application to Health,
Cognition and Social Signal Processing. I will also discuss the
problem of language grounding and show recent results.

Bio:

Yiannis Aloimonos is a Professor of Computational Vision and
Intelligence in the Dept. of Computer Science at the University of
Maryland, College Park and the Director of the Computer Vision
Laboratory at the Institute for Advanced Computer Studies. He works in
the fundamental aspects of Geometry and Statistics in the area of
multiple view vision (3D shape, segmentation, motion analysis). He is
known for his work on Active Vision and his study of vision as a
dynamic process. He has received several awards for his work
(including the Marr Prize Honorable Mention Award, 1st International
Conference on Computer Vision for his work on Active Vision and the
Presidential Young Investigator Award). His research has been
supported over the years by the European Union (Cognitive Systems),
NSF, NIH, ONR, DARPA, IBM, Honeywell, Dassault and Westinghouse. His
current interests are on the integration of vision, action and
cognition.