Reference : Random Subwindows for Robust Image Classification
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/12600
Random Subwindows for Robust Image Classification
English
Marée, Raphaël mailto [Université de Liège - ULg > Department of Electrical Engineering and Computer Science > Systèmes et Modélisation > >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Piater, Justus mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > INTELSIG Group >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Schmid, Cordelia [> > > >]
Soatto, Stefano [> > > >]
Tomasi, Carlo [> > > >]
2005
Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2005)
1
34--40
Yes
No
International
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
IEEE
San Diego
USA
[en] machine learning ; extra-trees ; random subwindows
[en] We present a novel, generic image classification method based on a recent machine learning algorithm (ensembles of extremely randomized decision trees). Images are classified using randomly extracted subwindows that are suitably normalized to yield robustness to certain image transformations. Our method is evaluated on four very different, publicly available datasets (COIL-100, ZuBuD, ETH-80, WANG). Our results show that our automatic approach is generic and robust to illumination, scale, and viewpoint changes. An extension of the method is proposed to improve its robustness with respect to rotation changes.
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
http://hdl.handle.net/2268/12600
http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2005/MGPW05
(Accepted as oral presentation. Oral acceptance rate is 6.5%, overall acceptance rate is 28%)

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