Aggregating Local Descriptors for Epigraphs Recognition
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-o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Bulgarian Academy of Sciences, Institute of Mathematics and Informatics
2014-09-01
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| Series: | Digital Presentation and Preservation of Cultural and Scientific Heritage |
| Subjects: | |
| Online Access: | https://dipp.math.bas.bg/dipp/article/view/347 |
| Summary: | 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-ofthe-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. |
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| ISSN: | 1314-4006 2535-0366 |