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Keyframe detection in visual lifelogs
Blighe, Michael; Doherty, Aiden R.; Smeaton, Alan F.; O'Connor, Noel E.
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.
Keyword(s): Lifelog; Multimedia systems; Image processing; health management; keyframe selection; visual diary
Publication Date:
2008
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Blighe, Michael, Doherty, Aiden R. ORCID: 0000-0003-4395-7702 <https://orcid.org/0000-0003-4395-7702>, Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <https://orcid.org/0000-0003-1028-8389> and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> (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
Publisher(s): Association for Computing Machinery
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/624/1/petra08.pdf,
http://doi.acm.org/10.1145/1389586.1389652
First Indexed: 2009-11-05 02:00:53 Last Updated: 2019-02-09 07:02:19