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Machine Vision and Applications

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30.03.2017 | Special Issue Paper

ISR: indoor shop recognition via user-friendly and efficient fingerprinting on smartphones

verfasst von: Dong Zhao, Huaiyu Xu, Jiaqi An, Liang Liu, Huadong Ma

Erschienen in: Machine Vision and Applications | Ausgabe 7/2017

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Abstract

Indoor shop recognition can not only help mobile users to quickly recognize a shop to know about the information of interest without needing to enter the shop, but also assist in achieving more accurate user localization in a shopping mall. However, the existing Wi-Fi fingerprint-based approaches or image-based approaches cannot accomplish this goal well due to a huge cost of constructing large-scale fingerprint database and poor accuracy. In order to address these issues, we proposed a user-friendly and efficient fingerprinting method to collect various valuable sensory data with smartphones, which can not only reduce the randomness of fingerprints and the negative impact of pedestrians in image matching, but also be used to derive the user-to-shop distance based on the perspective projection model for assisting in determining an accurate fingerprint searching scope. We also proposed an efficient fingerprint searching and matching method to improve the recognition accuracy. We implemented a prototype system and collected fingerprint datasets in a shopping mall. Extensive experiments demonstrate that our solution achieves promising results in realistic scenarios.

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Titel: ISR: indoor shop recognition via user-friendly and efficient fingerprinting on smartphones
verfasst von: Dong Zhao
Huaiyu Xu
Jiaqi An
Liang Liu
Huadong Ma
Publikationsdatum: 30.03.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Machine Vision and Applications / Ausgabe 7/2017
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI: https://doi.org/10.1007/s00138-017-0838-2

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