Geo-located Image Categorization and Location Recognition

Marco Cristani, Alessandro Perina, Umberto Castellani, Vittorio Murino



Image categorization is undoubtedly one of the most recent and challenging problems faced in Computer Vision. The scientific literature is plenty of methods more or less efficient and dedicated to a specific class of images; further, commercial systems are also going to be advertised in the market. Nowadays, additional data can also be attached to the images, enriching its semantic interpretation beyond the pure appearance. This is the case of geo-location data that contain information about the geographical place where an image has been acquired. This data allow, if not require, a different management of the images, for instance, to the purpose of easy retrieval from a repository, or of identifying the geographical place of an unknown picture, given a geo-referenced image repository. This paper constitutes a first step in this sense, presenting a method for geo-referenced image categorization, and for the recognition of the geographical location of an image without such information available. The solutions presented are based on robust pattern recognition techniques, such as the probabilistic Latent Semantic Analysis, the Mean Shift clustering and the Support Vector Machines. Experiments have been carried out on a couple of geographical image databases: results are actually very promising, opening new interesting challenges and applications in this research field.


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Paper Citation

in Harvard Style

Cristani M., Perina A., Castellani U. and Murino V. (2008). Geo-located Image Categorization and Location Recognition . In Proceedings of the 1st International Workshop on Image Mining Theory and Applications IMTA 2008 - Volume 1: IMTA, (VISIGRAPP 2008) ISBN 978-989-8111-25-8, pages 93-102. DOI: 10.5220/0002340400930102

in Bibtex Style

author={Marco Cristani and Alessandro Perina and Umberto Castellani and Vittorio Murino},
title={Geo-located Image Categorization and Location Recognition},
booktitle={Proceedings of the 1st International Workshop on Image Mining Theory and Applications IMTA 2008 - Volume 1: IMTA, (VISIGRAPP 2008)},

in EndNote Style

JO - Proceedings of the 1st International Workshop on Image Mining Theory and Applications IMTA 2008 - Volume 1: IMTA, (VISIGRAPP 2008)
TI - Geo-located Image Categorization and Location Recognition
SN - 978-989-8111-25-8
AU - Cristani M.
AU - Perina A.
AU - Castellani U.
AU - Murino V.
PY - 2008
SP - 93
EP - 102
DO - 10.5220/0002340400930102