BMVC 2004, Kingston, 7th-9th Sept, 2004

Unsupervised Learning of Multi-Object Events
S. Hongeng (University of Hamburg, Germany)

We present a novel approach for automatically inferring models of multiobject
events. Objects are first detected and tracked, their motion is then
segmented into a set of primitive events. These primitive events then form
the nodes in a Markov network that encodes the entire event space. A bottomup/
top-down search algorithm is developed to detect typical event structures
that are used for classifying an observed multi-object event. We demonstrate
our algorithm on clustering and inferring events in a table-laying scene.
(pdf article)