Title :
Video classification using a tree-based RBF network
Author :
Gillespie, W.J. ; Nguyen, D.T.
Author_Institution :
Dept. of Electr. Eng., Tasmania Univ., Hobart, Tas., Australia
Abstract :
We study in this paper the performance of a tree-based radial-basis function (TB-RBF) network when applied to video classification. In this network, the result of a binary classification tree is used to configure and to initialise the structure of the RBF network. Video shots in a database are classified into four video genres: sport, news, scenery, and drama. Experimental results show an improvement in classification accuracy compared to results previously presented by the authors using a generalised RBF network.
Keywords :
image classification; radial basis function networks; trees (mathematics); video signal processing; binary classification tree; classification accuracy; radial-basis function; tree-based RBF network; video classification; video database; Classification tree analysis; Content based retrieval; Database systems; Indexing; Information retrieval; Linear regression; Multilayer perceptrons; Neurons; Pattern recognition; Radial basis function networks;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530429
