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Validating the detection of everyday concepts in visual lifelogs

Byrne, Daragh and Doherty, Aiden R. and Snoek, Cees G.M. and Jones, Gareth J.F. and Smeaton, Alan F. (2008) Validating the detection of everyday concepts in visual lifelogs. In: SAMT 2008 - 3rd International Conference on Semantic and Multimedia Technologies, 3-5 December 2008, Koblenz, Germany. ISBN 978-3-540-92234-6

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The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a use s day-today activities. It can capture up to 3,000 images per day, equating to almost 1 million images per year. It is used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer s life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the novel domain of visual lifelogs. A concept detector models the correspondence between low-level visual features and highlevel semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept s presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept and to draw some interesting inferences on the lifestyles of those 5 users. We additionally present future applications of concept detection within the domain of lifelogging.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:SenseCam;
Subjects:Computer Science > Lifelog
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Published in:Semantic Multimedia. Lecture Notes in Computer Science 5392. Springer Berlin / Heidelberg. ISBN 978-3-540-92234-6
Publisher:Springer Berlin / Heidelberg
Official URL:
Copyright Information:© Springer-Verlag Berlin Heidelberg 2008
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, EU IST-CHORUS
ID Code:2205
Deposited On:09 Dec 2008 11:48 by Dr Aiden Doherty. Last Modified 13 Jan 2017 11:29

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