Publication Details
Shlukování založené na Voronoiově dláždění pro klasifikaci a vyhledávání ve videu
Burgetová Ivana, Ing., Ph.D. (DIFS)
Clustering, Classification, Video Search, Local Features
Although there are many clustering techniques, it is not possible to use them for
all purposes. The initiative problem was to create as many clusters as possible
(eg. thousands) for the local image features description in huge amount of video
for TRECVid 2008 evaluation. These large dimensional vectors cover the space
almost continuously and commonly used clustering methods are unable to create
enough classes or to finish in serious time.
Therefore, we have invented a new method based on Voronoi tessellation that needs
no more than two passes through the data. It is based on discovery of clusters in
higher density locations. Because of large dataset, it is possible to create
higher amount of candidate clusters and select appropriate number of classes
(large but not huge) and the rest data assign to these classes. The method has
been implemented as a set of SQL functions and queries and tested on a huge
problem and large amount of classes. Performed experiments have proven that it is
significantly faster than common techniques.
@inproceedings{BUT30195,
author="Petr {Chmelař} and Ivana {Burgetová}",
title="Shlukování založené na Voronoiově dláždění pro klasifikaci a vyhledávání ve videu",
booktitle="ZNALOSTI 2008, Proceedings of the 8th annual conference",
year="2009",
pages="71--82",
publisher="Vydavateľstvo STU",
address="Brno",
isbn="978-80-227-3015-0"
}