SenseCam image localisation using hierarchical SURF trees
Ó Conaire, Ciarán and Blighe, Michael and O'Connor, Noel E. (2009) SenseCam image localisation using hierarchical SURF trees. In: MMM 2009 - 15th International Multimedia Modeling Conference, 7-9 January 2009, Sophia-Antipolis, France. ISBN 978-3-540-92891-1
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The SenseCam is a wearable camera that automatically takes photos of the wearer's activities, generating thousands of images per day.
Automatically organising these images for efficient search and retrieval is a challenging task, but can be simplified by providing
semantic information with each photo, such as the wearer's location during capture time. We propose a method for automatically determining the wearer's location using an annotated image database, described using SURF interest point descriptors. We show that SURF out-performs SIFT in matching SenseCam images and that matching can be done efficiently using hierarchical trees of SURF descriptors. Additionally, by re-ranking the top images using bi-directional SURF matches, location matching performance is improved further.
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