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Investigating keyframe selection methods in the novel domain of passively captured visual lifelogs

Doherty, Aiden R. and Byrne, Daragh and Smeaton, Alan F. and Jones, Gareth J.F. and Hughes, Mark (2008) Investigating keyframe selection methods in the novel domain of passively captured visual lifelogs. In: CIVR 2008 - ACM International Conference on Image and Video Retrieval , 7-9 July 2008, Niagara Falls, Canada. ISBN 978-1-60558-070-8

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The SenseCam is a passive capture wearable camera, worn around the neck, and when worn continuously it takes an average of 1,900 images per day. It can be used to create a personal lifelog or visual recording of the wearer’s life which can be helpful as an aid to human memory. For such a large amount of visual information to be useful, it needs to be structured into “events”, which can be achieved through automatic segmentation. An important component of this structuring process is the selection of keyframes to represent individual events. This work investigates a variety of techniques for the selection of a single representative keyframe image from each event, in order to provide the user with an instant visual summary of that event. In our experiments we use a large test set of 2,232 lifelog events collected by 5 users over a time period of one month each. We propose a novel keyframe selection technique which seeks to select the image with the highest “quality” as the keyframe. The inclusion of “quality” approaches in keyframe selection is demonstrated to be useful owing to the high variability in image visual quality within passively captured image collections.

Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Uncontrolled Keywords:Image Quality Metrics; Keyframe Selection;
Subjects:Computer Science > Lifelog
Computer Science > Information storage and retrieval systems
Computer Science > Information retrieval
Computer Science > Image processing
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:Association for Computing Machinery
Official URL:
Copyright Information:© ACM, 2008. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 2008 international conference on Content-based image and video retrieval, {Pages 259-268, (2008)}
Funders:Microsoft Research, Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:636
Deposited On:08 Oct 2008 09:47 by Hyowon Lee. Last Modified 01 Feb 2017 11:21

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