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. © Springer-Verlag Berlin Heidelberg 2013.
Amato, G., & Falchi, F. (2013). On kNN Classification and Local Feature Based Similarity Functions. In Communications in Computer and Information Science (Vol. 271, pp. 224–239). Springer Verlag. https://doi.org/10.1007/978-3-642-29966-7_15