Global Priors of Place and Activity Tags

No. 4: Human Behavior Modeling

Volume

Papers from the 2009 AAAI Spring Symposium

Contents

This paper describes an approach for creating detailed full coverage labellings of human activity. Our goal is to create global maps of physical positions labelled with a distribution over the most likely place name and most likely activity. We ground our ontology of labels as: the term that a person would want to display to someone before they initiate a communication. Rather than compiling a canonical list of possible labels, we piggyback the label data collection in a situated communicative exchange. Using ideas inspired by image segmentation and extended to support our goals we propose machine learning techniques for smoothing distributions across gaps in existing data.