%0 Conference Proceedings
%T Approximate Convex Hulls Family for One-Class Cassification
%A Pierluigi Casale
%A Oriol Pujol
%A Petia Radeva
%E Carlo Sansone
%E Josef Kittler
%E Fabio Roli
%B 10th International Workshop on Multiple Classifier Systems
%D 2011
%V 6713
%I Springer Berlin Heidelberg
%@ 0302-9743
%@ 978-3-642-21556-8
%F Pierluigi Casale2011
%O MILAB;HuPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1761), last updated on Tue, 11 Mar 2014 16:33:56 +0100
%X In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification.
%U http://www.springerlink.com/index/0227J316800657T6.pdf
%U http://dx.doi.org/10.1007/978-3-642-21557-5_13
%P 106-115