Amato G., Falchi F., Rabitti F., Vadicamo L.
Inscriptions Recognition Object Recognition Content-Based Image Retrieval
In this paper, we consider the task of recognizing inscriptions in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 inscriptions, we used a ð'~-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in comparing state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating Scale Invariant Feature Transform descriptors is the best choice for this task.
Source: EAGLE 2014 - First EAGLE International Conference, pp. 117–131, Parigi, Francia, 29-30 September - 1 October 2014
Publisher: Casa Editrice Università La Sapienza, Roma, ITA
@inproceedings{oai:it.cnr:prodotti:295307, title = {Inscriptions visual recognition. A comparison of state-of-the-art object recognition approaches}, author = {Amato G. and Falchi F. and Rabitti F. and Vadicamo L.}, publisher = {Casa Editrice Università La Sapienza, Roma, ITA}, booktitle = {EAGLE 2014 - First EAGLE International Conference, pp. 117–131, Parigi, Francia, 29-30 September - 1 October 2014}, year = {2014} }
EAGLE
Europeana network of Ancient Greek and Latin Epigraphy