Abstract
This paper proposes a new efficient indoor localization method based on visual vocabulary. The special feature of this method is that no additional components are needed, but only mobile devices equipped with cameras. By matching the query image with a visual vocabulary constructed by a Bag of Self-Optimized-Ordered Visual Vocabulary (BoSOV), the user’s position can be accurately determined. In addition, the efficiency of our scheme is compared with that of other schemes, and simulation results reveal that our method has higher indoor positioning efficiency, especially when the amount of image data is large. Simulation results show that our method can well achieve efficient visual indoor positioning when the data volume is relatively large.
This work is supported by the National Natural Science Foundation of China (61771186), University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province (UNPYSCT-2017125), Distinguished Young Scholars Fund of Heilongjiang University, and postdoctoral Research Foundation of Heilongjiang Province (LBH-Q15121).
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Guo, R., Qin, D., Zhao, M., Xu, G. (2019). An Efficient Indoor Localization Method Based on Visual Vocabulary. In: Han, S., Ye, L., Meng, W. (eds) Artificial Intelligence for Communications and Networks. AICON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 286. Springer, Cham. https://doi.org/10.1007/978-3-030-22968-9_36
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DOI: https://doi.org/10.1007/978-3-030-22968-9_36
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