@inbook{6672af70a0b34983b0ea183c8953de8e,
title = "Indoor Localisation and Navigation on Augmented Reality Devices",
abstract = "We present a novel indoor mapping and localisation approach for Augmented Reality (AR) devices that exploits the fusion of iner- tial sensors with visual odometry. We have demonstrated the ap- proach using Google Glass (GG) and Google Cardboard (GC) sup- ported with an Android phone. Our work presents an application of Extended Kalman Filter (EKF) for sensor fusion for AR based application where previous work on Bag of Visual Words Pairs (BoVWP) [10] based image matching is used for bundle adjustment on Fused odometry. We present the empirical validation of this approach on three different indoor spaces in an office environment. We concluded that vision complimented with inertial data effectively compensate the ego-motion of the user, improving the accuracy of map generation and localisation",
keywords = "Human-centered computing [Interaction paradigms]: Mixed/augmented reality - ; Mathematics of computing [Probabilistic reasoning algorithms]: Kalman filters -",
author = "Gaurav Gupta and Nishant Kejriwal and Prasun Pallav and Ehtesham Hassan and Swagat Kumar and Ramya Hebbalaguppe",
year = "2017",
month = jan,
day = "30",
doi = "10.1109/ISMAR-Adjunct.2016.0052",
language = "English",
isbn = "9781509037407",
series = "Adjunct Proceedings of the 2016 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "107--112",
booktitle = "Adjunct Proceedings of the 2016 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2016",
address = "United States",
note = " 2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct) ; Conference date: 19-09-2016 Through 23-09-2016",
}