Automated management of more than one million lifelog images
Doherty, Aiden R. and Smeaton, Alan F. (2007) Automated management of more than one million lifelog images. In: Seminar at the School of Computing and Intelligent Systems (SCIS) and Computer Science Research Institute (CSRI), University of Ulster, 21 December 2007, Derry, Northern Ireland.
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The SenseCam is a passively capturing wearable camera that captures approximately 2,500 images on average per day. This provides a user with an extensive visual diary. Possible applications making use of this device include helping dementia sufferers recall events from short-term memory, and also this device can be used by tourists to maintain an extensive image collection of particular trips. However a large image collection will quickly build up, with an average of 1 million images captured each year. This presents a considerable challenge in terms of managing such a large collection and to make it accessible for users. My research proposes to address this problem in 4 steps:
1) Identifying distinct events within the 2,500 images that are captured daily
2) Highlighting the most unique of those events
3) Finding similar events to a given event
4) Augmenting the low-quality images from the wearable camera with higher quality images from external sources.
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