Combining Face Detection and Novelty to Identify Important Events in a Visual Lifelog

  • Authors:

  • Aiden R. Doherty;Alan F. Smeaton

  • Affiliations:

  • -;-

  • Venue:
  • CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
  • Year:
  • 2008

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Abstract

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.