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Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images

Doherty, Aiden R. (2009) Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images. PhD thesis, Dublin City University.

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Abstract

Lifelogging is an area of research which is concerned with the capture of many aspects of an individual's life digitally, and within this rapidly emerging field is the significant challenge of managing images passively captured by an individual of their daily life. Possible applications vary from helping those with neurodegenerative conditions recall events from memory, to the maintenance and augmentation of extensive image collections of a tourist's trips. However, a large lifelog of images can quickly amass, with an average of 700,000 images captured each year, using a device such as the SenseCam. We address the problem of managing this vast collection of personal images by investigating automatic techniques that: 1. Identify distinct events within a full day of lifelog images (which typically consists of 2,000 images) e.g. breakfast, working on PC, meeting, etc. 2. Find similar events to a given event in a person's lifelog e.g. "show me other events where I was in the park" 3. Determine those events that are more important or unusual to the user and also select a relevant keyframe image for visual display of an event e.g. a "meeting" is more interesting to review than "working on PC" 4. Augment the images from a wearable camera with higher quality images from external "Web 2.0" sources e.g. find me pictures taken by others of the U2 concert in Croke Park In this dissertation we discuss novel techniques to realise each of these facets and how effective they are. The significance of this work is not only of benefit to the lifelogging community, but also to cognitive psychology researchers studying the potential benefits of lifelogging devices to those with neurodegenerative diseases.

Item Type:Thesis (PhD)
Date of Award:March 2009
Refereed:No
Supervisor(s):Smeaton, Alan F.
Subjects:Computer Science > Lifelog
Computer Science > Information storage and retrieval systems
Computer Science > Multimedia systems
Computer Science > Information retrieval
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
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
Funders:Irish Research Council for Science Engineering and Technology, Science Foundation Ireland
ID Code:2270
Deposited On:02 Apr 2009 17:40 by Alan F. Smeaton. Last Modified 16 Nov 2009 17:31

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