Title: Visual mining – interpreting image and video
Abstract:
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.
Speaker:
|
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 |
