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Content vs. context for multimedia semantics: the case of SenseCam image structuring

Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2006) Content vs. context for multimedia semantics: the case of SenseCam image structuring. In: SAMT 2006 - Proceedings of The First International Conference on Semantics And Digital Media Technology, 6-8 December 2006, Athens, Greece. ISBN 978-3-540-49335-8

Abstract
Much of the current work on determining multimedia semantics from multimedia artifacts is based around using either context, or using content. When leveraged thoroughly these can independently provide content description which is used in building content-based applications. However, there are few cases where multimedia semantics are determined based on an integrated analysis of content and context. In this keynote talk we present one such example system in which we use an integrated combination of the two to automatically structure large collections of images taken by a SenseCam, a device from Microsoft Research which passively records a person’s daily activities. This paper describes the post-processing we perform on SenseCam images in order to present a structured, organised visualisation of the highlights of each of the wearer’s days.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The original publication is available at www.springerlink.com.
Subjects:Computer Science > Multimedia systems
DCU Faculties and Centres:Research Institutes and Centres > Centre for Digital Video Processing (CDVP)
Research Institutes and Centres > Adaptive Information Cluster (AIC)
Published in: Semantic Multimedia. Lecture Notes in Computer Science 4306. Springer Berlin / Heidelberg. ISBN 978-3-540-49335-8
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/11930334_1
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, Microsoft Research
ID Code:287
Deposited On:11 Mar 2008 by DORAS Administrator . Last Modified 08 Nov 2018 10:43
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