Abstract
The ability to identify the artworks that a museum visitor is looking at, using first-person images seamlessly captured by wearable cameras can be used as a means for invoking applications that provide information about the exhibits, and provide information about visitors’ activities. As part of our efforts to optimize the artwork recognition accuracy of an artwork identification system under development, an investigation aiming to determine the effect of different conditions on the artwork recognition accuracy in a gallery/exhibition environment is presented. Through the controlled introduction of different distractors in a virtual museum environment, it is feasible to assess the effect on the recognition performance of different conditions. The results of the experiment are important for improving the robustness of artwork recognition systems, and at the same time the conclusions of this work can provide specific guidelines to curators, museum professionals and visitors, that will enable the efficient identification of artworks, using images captured with wearable cameras in a museum environment.
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Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 739578 complemented by the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development. We also like to thank the personnel of the State Gallery of Contemporary Cypriot Art for their support.
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Lanitis, A., Theodosiou, Z., Partaourides, H. (2021). Artwork Identification in a Museum Environment: A Quantitative Evaluation of Factors Affecting Identification Accuracy. In: Ioannides, M., Fink, E., Cantoni, L., Champion, E. (eds) Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2020. Lecture Notes in Computer Science(), vol 12642. Springer, Cham. https://doi.org/10.1007/978-3-030-73043-7_50
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