PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The influence of hubness in nearest-neighbor methods in object recognition
Nenad Tomašev, Raluca Brehar, Dunja Mladenić and Sergiu Nedevschi
In: ICCP 2011, 25-27 Aug 2011, Cluj-Napoca, Romania.

Abstract

Object recognition from images is one of the essential problems in automatic image processing. In this paper we focus specifically on nearest neighbor methods, which are widely used in many practical applications, not necessarily related to image data. It has recently come to attention that high dimensional data also exhibit high hubness, which essentially means that some very influential data points appear and these points are referred to as hubs. Unsurprisingly, hubs play a very important role in the nearest neighbor classification. We examine the hubness of various image data sets, under several different feature representations. We also show that it is possible to exploit the observed hubness and improve the recognition accuracy.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Brain Computer Interfaces
ID Code:8717
Deposited By:Jan Rupnik
Deposited On:21 February 2012