CINECA IRIS Institutional Research Information System
IRIS è la piattaforma adottata dall’Università degli Studi di Udine per gestire l’archivio aperto dei prodotti della ricerca. L’archivio contiene articoli, contributi in volume, monografie, interventi pubblicati in atti di convegno, Tesi di dottorato e altri materiali.
EnglishThis paper reports a novel approach to deal with the problem of Object and Scene recognition extending the traditional Bag of Words approach in two ways. Firstly, a dataset independent method of summarizing local features, based on multivariate Gaussian descriptors, is employed. Secondly, a recently proposed classification technique, particularly suited for high dimensional feature spaces without any dimensionality reduction step, allows to effectively exploit these features. Experiments are performed on two publicly available datasets and demonstrate the effectiveness of our approach when compared to state-of-the-art methods.
| Titolo: | Truncated Isotropic Principal Component Classifier for Image Classification | |
| Autori: | ||
| Data di pubblicazione: | 2014 | |
| Abstract: | This paper reports a novel approach to deal with the problem of Object and Scene recognition extending the traditional Bag of Words approach in two ways. Firstly, a dataset independent method of summarizing local features, based on multivariate Gaussian descriptors, is employed. Secondly, a recently proposed classification technique, particularly suited for high dimensional feature spaces without any dimensionality reduction step, allows to effectively exploit these features. Experiments are performed on two publicly available datasets and demonstrate the effectiveness of our approach when compared to state-of-the-art methods. | |
| Handle: | http://hdl.handle.net/11390/1105603 | |
| ISBN: | 978-1-4799-5750-7 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11390/1105603
Copyright © 2021