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2007 IEEE 23rd International Conference on Data Engineering
ProVeR: Probabilistic Video Retrieval using the Gauss-Tree
Istanbul, Turkey
April 15-April 20
ISBN: 1-4244-0802-4
ASCII Text
x 
 
Christian Bohm, Michael Gruber, Peter Kunath, Alexey Pryakhin, Matthias Schubert, "ProVeR: Probabilistic Video Retrieval using the Gauss-Tree," Data Engineering, International Conference on, pp. 1521-1522, 2007 IEEE 23rd International Conference on Data Engineering, 2007.
 
 
BibTex
x
 
@article{ 10.1109/ICDE.2007.369063,
author = {Christian Bohm and Michael Gruber and Peter Kunath and Alexey Pryakhin and Matthias Schubert},
title = {ProVeR: Probabilistic Video Retrieval using the Gauss-Tree},
journal ={Data Engineering, International Conference on},
volume = {0},
year = {2007},
isbn = {1-4244-0802-4},
pages = {1521-1522},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDE.2007.369063},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Engineering, International Conference on
TI - ProVeR: Probabilistic Video Retrieval using the Gauss-Tree
SN - 1-4244-0802-4
SP1521
EP1522
A1 - Christian Bohm,
A1 - Michael Gruber,
A1 - Peter Kunath,
A1 - Alexey Pryakhin,
A1 - Matthias Schubert,
PY - 2007
KW - null
VL - 0
JA - Data Engineering, International Conference on
ER -
 
Christian Bohm, Institute for Informatics, University of Munich, D-80538 Munich, Germany, boehm@dbs.ifi.lmu.de
Michael Gruber, Institute for Informatics, University of Munich, D-80538 Munich, Germany, gruber@dbs.ifi.lmu.de
Peter Kunath, Institute for Informatics, University of Munich, D-80538 Munich, Germany,kunath@dbs.ifi.lmu.de
Alexey Pryakhin, Institute for Informatics, University of Munich, D-80538 Munich, Germany, pryakhin@dbs.ifi.lmu.de
Matthias Schubert, Institute for Informatics, University of Munich, D-80538 Munich, Germany, schubert@dbs.ifi.lmu.de
Modeling objects by probability density functions (pdf) is a new powerful method to represent complex objects in databases. By representing an object as a pdf, e.g. a Gaussian, it is possible to represent very large and complex objects in a compact and still descriptive way. In this contribution, we propose ProVeR a prototype search engine for content-based video retrieval which represents a video as a set of Gaussians. The Gaussians are managed by the Gauss-tree, an index structure allowing the efficient processing of probabilistic queries. ProVeR provides even non-expert users with an intuitive method for efficient, content-based retrieval of videos containing similar shots and scenes.
Citation:
Christian Bohm, Michael Gruber, Peter Kunath, Alexey Pryakhin, Matthias Schubert, "ProVeR: Probabilistic Video Retrieval using the Gauss-Tree," icde, pp.1521-1522, 2007 IEEE 23rd International Conference on Data Engineering, 2007
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