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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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Abstract

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.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Image matching; SenseCam; localisation; SURF;
Subjects:Computer Science > Image processing
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/978-3-540-92892-8_4
Copyright Information:The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:2248
Deposited On:19 Jan 2009 14:38 by Ciaran O Conaire. Last Modified 05 Mar 2009 13:58

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