期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2018
卷号：14
期号：2
页码：1-11
DOI：10.1177/1550147718757664
出版社：Hindawi Publishing Corporation
摘要：In this article, we propose a new indoor positioning algorithm using smartphones, where wireless signals and images are deeply combined together to improve the positioning performance. Our approach is based on the use of local binary patterns’ feature, which has the advantages of rotation invariance and scale invariance. Moreover, the term “uniform” are fundamental properties of local image textures and their occurrence histogram is proven to be a very powerful texture feature. Besides, the received signal strength acts as a reliable cue on a person’s identity. We first obtain a coarse-grained estimation based on the visualization of wireless signals, which are presented by a vector, making use of fingerprinting methods. Then, we perform a matching process to determine correspondences between two-dimensional pixels and three-dimensional points based on images collected by the smartphone. After being evaluated by experiments, our proposed method demonstrates that the combination of the visual and the wireless data significantly improves the positioning accuracy and robustness. It can be widely applied to smartphones to better analyze human behavior and offer high-accuracy indoor location–based services.
关键词：Indoor positioning; information fusion; smartphones; wireless signals; image features
