Keynote Speaker

Title: Visual mining – interpreting image and video


Like text mining, visual media mining tries to make sense of the
world through algorithms – albeit by analysing pixels instead of words.
This talk highlights recent important technical advances in automated
media understanding, which has a variety of applications ranging from
machines emulating the human aesthetic judgment of photographs to typical
visual mining tasks such as analysing food images. Highlighted techniques
include near-duplicate detection, multimedia indexing and the role of
machine learning. While the first two enable visual search engines so
that, eg, a snapshot of a smart-phone alone links the real world to
databases with information about it, machine learning ultimately is the
key to endowing machines with human capabilities of recognition and
interpretation. The talk will end by looking into the crystal ball
exploring what machines might learn from automatically analysing tens of
thousands of hours of TV footage.


Stefan Rüger

Stefan Rüger is a Professor of Knowledge Media at the Knowledge Media Institute of The Open University . He read Physics at Freie Universität Berlin and
gained his PhD in Computer Science at Technische Universität Berlin (1996)
on the Theory of Neural Networks. During the next decade he carved out his
academic career from postdoc to Reader researching multimedia information
retrieval at Imperial College London, University of London, where he also
held an EPSRC Advanced Research Fellowship (1999-2004). In 2006 Stefan
became a Professor of Knowledge Media when he joined The Open University’s
Knowledge Media Institute to cover the area of Multimedia and Information
Systems. He currently holds an Honorary Professorship from the University
of Waikato, New Zealand, and has held Visiting Fellowships at Imperial
College London and Cranfield University, UK. Stefan is interested in the
intellectual challenge of visual processing with a view to automated
multimedia understanding