DocumentCode :
2132763
Title :
Accurate detection of real-world social interactions with smartphones
Author :
Palaghias, Niklas ; Hoseinitabatabaei, Seyed Amir ; Nati, Michele ; Gluhak, Alexander ; Moessner, Klaus
Author_Institution :
Institute for Communication Systems, University of Surrey, Guildford, GU2 7XH UK
fYear :
2015
fDate :
8-12 June 2015
Firstpage :
579
Lastpage :
585
Abstract :
Quantifying social interactions requires accurate, reliable and real-time recognition, of both users´ interpersonal distance and relative orientation. DARSIS is the outcome of our research towards fulfilling these requirements based upon a non-intrusive opportunistic mechanism that solely relies on sensors and communication capabilities of off-the-shelf smartphones. We developed a novel hierarchical classifier for interpersonal distance estimation, produced by a substantive training set of Bluetooth Received Signal Strength Indicator (RSSI) and a concrete feature selection process. The presented relative orientation estimation mechanism addresses problems associated with lack of facing direction information in prior works, independently of the wearing position. In addition, DARSIS introduces a collaborative sensing scheme which allows on-the-fly exchange of facing direction information between users and facilitates the interpersonal distance recognition process by sharing RSSI values among devices. We show that the proposed interpersonal distance estimation models outperform state-of-the-art solutions and achieve up to 93.52% accuracy while DARSIS as a coherent system detects accurately 81.40% of the interactions in a real-world environment.
Keywords :
Accuracy; Bluetooth; Estimation; Performance evaluation; Sensors; Smart phones; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2015 IEEE International Conference on
Conference_Location :
London, United Kingdom
Type :
conf
DOI :
10.1109/ICC.2015.7248384
Filename :
7248384
Link To Document :
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