Abstract
Wearable cameras can daily gather large amounts of image data that require powerful image indexing and retrieval techniques in order to find the information of interest. In this work, we address the indexing problem of egocentric data by exploring the relevance of different information sources provided by Convolutional Neural Networks (CNN) combined with image metadata. The proposed method was tested on a public egocentric dataset of 45.000 images and gave encouraging results.
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Oliveira-Barra, G., Dimiccoli, M., Radeva, P. (2017). Leveraging Activity Indexing for Egocentric Image Retrieval. In: Alexandre, L., Salvador Sánchez, J., Rodrigues, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2017. Lecture Notes in Computer Science(), vol 10255. Springer, Cham. https://doi.org/10.1007/978-3-319-58838-4_33
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DOI: https://doi.org/10.1007/978-3-319-58838-4_33
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