Paper published in a book (Scientific congresses and symposiums)
Fast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees
Dumont, Marie; Marée, Raphaël ; Wehenkel, Louis et al. 2009 • In Proc. International Conference on Computer Vision Theory and Applications (VISAPP) Peer reviewed
[en] This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of annotated images in order to train a subwindow annotation model by using the extremely randomized trees ensemble method appropriately extended to handle high-dimensional output spaces. The annotation of a pixel of an unseen image is done by aggregating the annotations of its subwindows containing this pixel. The proposed method is compared to a more basic approach predicting the class of a pixel from a single window centered on that pixel and to other state-of-the-art image annotation methods. In terms of accuracy, the proposed method significantly outperforms the basic method and shows good performances with respect to the state-of-the-art, while being more generic, conceptually simpler, and of higher computational efficiency than these latter.
Disciplines :
Computer science
Author, co-author :
Dumont, Marie; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst. Montefiore) > Systèmes et Modélisation
F.R.S.-FNRS - Fonds de la Recherche Scientifique FEDER - Fonds Européen de Développement Régional BELSPO - SPP Politique scientifique - Service Public Fédéral de Programmation Politique scientifique
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