PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Amato G., Falchi F. On kNN classification and local feature based similarity functions. Joaquim Felipe, Ana Fred (eds.). (Communications in Computer and Information Science, vol. 271). Heidelberg: Springer, 2013.
 
 
Abstract
(English)
In this paper we consider the problem of image content recognition and we address it by using local features and kNN based classification strategies. Specifically, we define a number of image similarity functions relying on local features comparing their performance when used with a kNN classifier. Furthermore, we compare the whole image similarity approach with a novel two steps kNN based classification strategy that first assigns a label to each local feature in the document to be classified and then uses this information to assign a label to the whole image. We perform our experiments solving the task of recognizing landmarks in photos.
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-29966-7_15
DOI: 10.1007/978-3-642-29966-7_15
Subject Image classification
Local feature
Multimedia information retrieval
kNN
H.3.3 Information Search and Retrieval


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