Research Article
SURFtogether: Towards Context Proximity Detection Using Visual Features
@INPROCEEDINGS{10.4108/icst.iccasa.2014.257255, author={Marco Maier and Chadly Marouane and Manuel Klette and Florian Dorfmeister and Philipp Marcus and Claudia Linnhoff-Popien}, title={SURFtogether: Towards Context Proximity Detection Using Visual Features}, proceedings={3rd International Conference on Context-Aware Systems and Applications}, publisher={ACM}, proceedings_a={ICCASA}, year={2015}, month={3}, keywords={context awareness proximity detection surf}, doi={10.4108/icst.iccasa.2014.257255} }- Marco Maier
Chadly Marouane
Manuel Klette
Florian Dorfmeister
Philipp Marcus
Claudia Linnhoff-Popien
Year: 2015
SURFtogether: Towards Context Proximity Detection Using Visual Features
ICCASA
ACM
DOI: 10.4108/icst.iccasa.2014.257255
Abstract
With the now near ubiquity of smart mobile devices and the advent of new wearable computing devices like Google Glass, context-aware computing applications are becoming more and more feasible. We propose a new concept coined Context-Proximity Awareness aimed at identifying closely related entities based on contextual similarity. As a first step towards that goal, we introduce the SURFtogether approach, trying to detect contextual proximity by analyzing the field of vision of two or more entities. We evaluate the general feasibility of our approach based on real-world data and show that in our initial tests, correct detection of contextual proximity is achieved nearly 90% of the time.
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