Combining face detection and novelty to identify important events in a visual lifelog
Doherty, Aiden R. and Smeaton, Alan F. (2008) Combining face detection and novelty to identify important events in a visual lifelog. In: CIT 2008 - IEEE International Conference on Computer and Information Technology, Workshop on Image- and Video-based Pattern Analysis and Applications, 8-11 July 2008, Sydney, Australia. ISBN 978-0-7695-3242-4
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The SenseCam is a passively capturing wearable camera, worn around the neck and takes an average of almost 2,000 images per day, which equates to over 650,000 images per year. It is used to create a personal lifelog or visual recording of the wearer’s life and generates information which can be helpful as a human memory aid. For such a large amount of visual information to be of any use, it is accepted that it should be structured into “events”, of which there are about 8,000 in a wearer’s average year. In automatically segmenting SenseCam images into events, it is desirable to automatically emphasise more important events and decrease the emphasis on mundane/routine events. This paper introduces the concept of novelty to help determine the importance of events in a lifelog. By combining novelty with face-to-face conversation detection, our system improves on previous approaches. In our experiments we use a large set of lifelog images, a total of 288,479 images collected by 6 users over a time period of one month each.
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