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SpeCam: sensing surface color and material with the front-facing camera of mobile device

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Quigley_2017_HCIMDS_SpeCam_AAM.pdf (15.00Mb)
Date
04/09/2017
Author
Yeo, Hui Shyong
Lee, Juyoung
Bianchi, Andrea
Harris-Birtill, David
Quigley, Aaron John
Keywords
Surface detection
Material detection
Discreet interaction
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology
DAS
BDC
R2C
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Abstract
SpeCam is a lightweight surface color and material sensing approach for mobile devices which only uses the front-facing camera and the display as a multi-spectral light source. We leverage the natural use of mobile devices (placing it face-down) to detect the material underneath and therefore infer the location or placement of the device. SpeCam can then be used to support discreet micro-interactions to avoid the numerous distractions that users daily face with today's mobile devices. Our two-parts study shows that SpeCam can i) recognize colors in the HSB space with 10 degrees apart near the 3 dominant colors and 4 degrees otherwise and ii) 30 types of surface materials with 99% accuracy. These findings are further supported by a spectroscopy study. Finally, we suggest a series of applications based on simple mobile micro-interactions suitable for using the phone when placed face-down.
Citation
Yeo , H S , Lee , J , Bianchi , A , Harris-Birtill , D & Quigley , A J 2017 , SpeCam: sensing surface color and material with the front-facing camera of mobile device . in Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '17) . , 25 , ACM , New York, NY , pp. 1-9 , 19th International Conference on Human-Computer Interaction with Mobile Devices and Services , Vienna , Austria , 4/09/17 . https://doi.org/10.1145/3098279.3098541
 
conference
 
Publication
Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '17)
DOI
https://doi.org/10.1145/3098279.3098541
Type
Conference item
Rights
Copyright © 2017, ACM. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1145/3098279.3098541
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/11620

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