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On kNN classification and local feature based similarity functions

Chapter
Publication Date:
2013
abstract:
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.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Image classification; Local feature; Multimedia information retrieval; kNN; H.3.3 Information Search and Retrieval
List of contributors:
Amato, Giuseppe; Falchi, Fabrizio
Authors of the University:
AMATO GIUSEPPE
FALCHI FABRIZIO
Handle:
https://iris.cnr.it/handle/20.500.14243/254821
Book title:
Agents and Artificial Intelligence
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Overview

URL

http://link.springer.com/chapter/10.1007%2F978-3-642-29966-7_15
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