Amato G., Falchi F., Rabitti F., Vadicamo L.
Inscriptions Visual Recognition Object Recognition Content-Based Image Retrieval Bag-of-Features VLAD
In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating 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 SIFT descriptors is the best choice for this task.
Source: The Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage, pp. 49–58, Veliko Tarnovo, Bulgaria, 18-21 September 2014
@inproceedings{oai:it.cnr:prodotti:295708, title = {Aggregating local descriptors for epigraphs recognition}, author = {Amato G. and Falchi F. and Rabitti F. and Vadicamo L.}, booktitle = {The Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage, pp. 49–58, Veliko Tarnovo, Bulgaria, 18-21 September 2014}, year = {2014} }
EAGLE
Europeana network of Ancient Greek and Latin Epigraphy