Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5561
Title: An adaptive smoothing method for sensor noise in augmented reality applications on smartphones
Authors: Özcan, R.
Orhan, F.
Demirci, Muhammed Fatih
Abul, O.
Keywords: Augmented reality
noise
sensors
smoothing
Source: 4th International ICST Conference on Mobile Wireless Middleware, Operating Systems, and Applications, MobilWare 2011, 22 June 2011 through 24 June 2011, London, 90407
Abstract: Handling inaccurate and noisy sensor readings are among important challenges while implementing augmented reality applications on smartphones. As a result, we need to smooth the sensor readings for steady operation. However, no smoothing algorithm performs best in all cases as there is an inherent tradeoff. On one hand, excessive smoothing slows down the effect of device movements, hence makes applications less responsive. On the other hand, insufficient smoothing causes objects on the screen to constantly move back and forth even while the device is steady, hence makes applications too responsive. Clearly, both of the extremes cause augmented reality applications to be less effective in terms of human-computer interaction performance. In this paper, we propose an adaptive smoothing method based on the rate of change in device view direction. Basically, the method adjusts the smoothing level adaptively based on the phone movement. Our experimental results show that our adaptive approach, in comparison to previous proposals, achieves a better smoothing for various cases of phone movements. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.
URI: https://doi.org/10.1007/978-3-642-30607-5_19
https://hdl.handle.net/20.500.11851/5561
ISBN: 9783642306068
ISSN: 1867-8211
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Show full item record



CORE Recommender

SCOPUSTM   
Citations

3
checked on Nov 2, 2024

Page view(s)

106
checked on Nov 4, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.