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Combining face detection and novelty to identify important events in a visual lifelog

Doherty, Aiden R. orcid logoORCID: 0000-0003-4395-7702 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (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

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:face detection; image management; novelty detection;
Subjects:Computer Science > Lifelog
Computer Science > Information storage and retrieval systems
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
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/CIT.2008.Workshops.31
Copyright Information:©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Funders:Microsoft Research, Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:638
Deposited On:08 Oct 2008 09:11 by Hyowon Lee . Last Modified 04 Oct 2018 11:29
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