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Exploiting context information to aid landmark detection in SenseCam images

Blighe, Michael, Le Borgne, Hervé orcid logoORCID: 0000-0003-0520-8436, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135, Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 and Jones, Gareth J.F. orcid logoORCID: 0000-0003-2923-8365 (2006) Exploiting context information to aid landmark detection in SenseCam images. In: ECHISE 2006 - 2nd International Workshop on Exploiting Context Histories in Smart Environments - Infrastructures and Design, 17 September 2006, Orange County, CA, USA.

Abstract
In this paper, we describe an approach designed to exploit context information in order to aid the detection of landmark images from a large collection of photographs. The photographs were generated using Microsoft’s SenseCam, a device designed to passively record a visual diary and cover a typical day of the user wearing the camera. The proliferation of digital photos along with the associated problems of managing and organising these collections provide the background motivation for this work. We believe more ubiquitious cameras, such as SenseCam, will become the norm in the future and the management of the volume of data generated by such devices is a key issue. The goal of the work reported here is to use context information to assist in the detection of landmark images or sequences of images from the thousands of photos taken daily by SenseCam. We will achieve this by analysing the images using low-level MPEG-7 features along with metadata provided by SenseCam, followed by simple clustering to identify the landmark images.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Additional Information:Workshop held in conjunction with UbiComp 2006 - 8th International Conference of Ubiquitous Computing
Uncontrolled Keywords:SenseCam; context; low-level features; clustering; landmark images;
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > Adaptive Information Cluster (AIC)
Official URL:http://echise.ipsi.fhg.de/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Commission FP6-027026, aceMedia Project FP6-001765,, Microsoft Research, Science Foundation Ireland, SFi 03/IN.3/I361
ID Code:422
Deposited On:04 Apr 2008 by DORAS Administrator . Last Modified 09 Nov 2018 10:31
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