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Keyframe detection in visual lifelogs

Blighe, Michael and Doherty, Aiden R. and Smeaton, Alan F. and O'Connor, Noel E. (2008) Keyframe detection in visual lifelogs. In: Proceedings of the 1st ACM international conference on PErvasive Technologies Related to Assistive Environments, July 2008, Athens, Greece. ISBN 978-1-60558-067-8

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Abstract

The SenseCam is a wearable camera that passively captures images. Therefore, it requires no conscious effort by a user in taking a photo. A Visual Diary from such a source could prove to be a valuable tool in assisting the elderly, individuals with neurodegenerative diseases, or other traumas. One issue with Visual Lifelogs is the large volume of image data generated. In previous work we spit a day's worth of images into more manageable segments, i.e. into distinct events or activities. However, each event coud stil consist of 80-100 images. thus, in this paper we propose a novel approach to selecting the key images within an event using a combination of MPEG-7 and Scale Invariant Feature Transform (SIFT) features.

Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:health management; keyframe selection; visual diary;
Subjects:Computer Science > Lifelog
Computer Science > Multimedia systems
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Publisher:Association for Computing Machinery
Official URL:http://doi.acm.org/10.1145/1389586.1389652
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:624
Deposited On:06 Oct 2008 17:10 by Alan F. Smeaton. Last Modified 30 Jun 2009 09:48

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