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.
Inscriptions visual recognition. A comparison of state-of-the-art object recognition approaches
Falchi, Fabrizio;Vadicamo, Lucia
2014-01-01
Abstract
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.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.