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7 June 2023 Crowd-sourced optical indoor positioning updated by WiFi fingerprint localization
Yaoyu Li, Hua He, Fei Hou
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Proceedings Volume 12701, Fifteenth International Conference on Machine Vision (ICMV 2022); 127011R (2023) https://doi.org/10.1117/12.2679360
Event: Fifteenth International Conference on Machine Vision (ICMV 2022), 2022, Rome, Italy
Abstract
Image matching and wireless signal fingerprint are two methods to realize indoor localization. However, the method based on image-matching needs to build a large scale image database, the process of matching tends to be high computing complexity, which cannot satisfy the requirements of real time. Meanwhile, WiFi signal fingerprint is affected easily by changing surroundings, so the positioning accuracy and stability are not so perfect. The process of database building is time-consuming and laborious. To address these issues, we propose a crowd-sourced optical indoor positioning algorithm updated by WiFi fingerprint. At first, we use WiFi fingerprint based on K Weighted Nearest Neighbor (KWNN) algorithm to make a coarse estimation, which will reduce the scope of image retrieval during image matching stage, then fuse image and posture data based on mean-weighted exponent algorithm to refine the previous coarse estimation. We also update the positioning database in a crowd-sourced way. Experimental results show that the mean error of the proposed algorithm can reach 1.71m, under the condition of real-time calculating, which decreases by 50% compared with the standard KWNN algorithm. Meanwhile, the positioning stability has improved greatly.
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Yaoyu Li, Hua He, and Fei Hou "Crowd-sourced optical indoor positioning updated by WiFi fingerprint localization", Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 127011R (7 June 2023); https://doi.org/10.1117/12.2679360
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KEYWORDS
Databases
Image processing
Image sensors
Cell phones
Algorithm development
Image retrieval
Image fusion
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