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Sensors 2010, 10(3), 1423-1446; doi:10.3390/s100301423

Automatically Augmenting Lifelog Events Using Pervasively Generated Content from Millions of People

*  and
Centre for Sensor Web Technologies, Dublin City University, Glasnevin, Dublin 9, Ireland
* Author to whom correspondence should be addressed.
Received: 24 December 2009 / Revised: 19 January 2010 / Accepted: 3 February 2010 / Published: 26 February 2010
(This article belongs to the Section Chemical Sensors)
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In sensor research we take advantage of additional contextual sensor information to disambiguate potentially erroneous sensor readings or to make better informed decisions on a single sensor’s output. This use of additional information reinforces, validates, semantically enriches, and augments sensed data. Lifelog data is challenging to augment, as it tracks one’s life with many images including the places they go, making it non-trivial to find associated sources of information. We investigate realising the goal of pervasive user-generated content based on sensors, by augmenting passive visual lifelogs with “Web 2.0” content collected by millions of other individuals.
Keywords: lifelogging; event augmentation; SenseCam; Web 2.0 lifelogging; event augmentation; SenseCam; Web 2.0
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Doherty, A.R.; Smeaton, A.F. Automatically Augmenting Lifelog Events Using Pervasively Generated Content from Millions of People. Sensors 2010, 10, 1423-1446.

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