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Exploring city structure from georeferenced photos using graph centrality measures

 
: Vrotsou, Katerina; Andrienko, Natalia; Andrienko, Gennady; Jankowski, Piotr

:
Volltext urn:nbn:de:0011-n-1945625 (138 KByte PDF)
MD5 Fingerprint: c711be418fecf670a72cb131e76bcf2f
The original publication is available at springerlink.com
Erstellt am: 8.3.2012


Gunopulos, D.:
Machine learning and knowledge discovery in databases. European conference, ECML PKDD 2011. Pt.3 : Athens, Greece, September 5-9, 2011; proceedings
Berlin: Springer, 2011 (Lecture Notes in Artificial Intelligence 6913)
ISBN: 3-642-23807-6
ISBN: 978-3-642-23807-9
ISBN: 978-3-642-23808-6
ISSN: 0302-9743
S.654-657
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) <2011, Athens>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
graph theory; georeferenced photo captures; city structure

Abstract
We explore the potential of applying graph theory measures of centrality to the network of movements extracted from sequences of georeferenced photo captures in order to identify interesting places and explore city structure. We adopt a systematic procedure composed of a series of stages involving the combination of computational methods and interactive visual analytics techniques. The approach is demonstrated using a collection of Flickr photos from the Seattle metropolitan area.

: http://publica.fraunhofer.de/dokumente/N-194562.html