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DTransfer: extremely low cost localization irrelevant to targets and regions for activity recognition

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Abstract

Multiple location-based device-free activity recognition systems indicate that some activities related to specific locations can be inferred from the location system and adding location information can improve the accuracy of activity recognition. Therefore, localization technology is the basis for activity recognition and other applications. Radio-Map is an effective measure in Device-free localization (DFL). Traditional fingerprint systems that can provide such accuracy are suffering from human cost in Radio-Map construction and update. Although the human cost in update phase has been paid attention, the higher costs caused by the initially created are ignored. In addition, existing systems assume that RSS change measurements caused by different targets are fixed distribution in any region. The two drawbacks will greatly affect the practicability and robustness of Radio-Map. In this paper, we propose, DTransfer, an extremely low-cost DFL approach that localize different kinds of targets in different regions. We design an optimized low-rank matrix completion model based on singular value decomposition (SVD) to construct the sensing matrix (i.e., radio-map) of the original region, which greatly reduces the overhead. Next, we employ a rigorously designed quadratic transfer scheme to accurately locate different categories of targets in different regions. Finally, we apply the location information to the activity recognition algorithm; experiments have shown that the accuracy of the algorithm for adding location information is increased by approximately 6%. Extensive experimental results illustrate that DTransfer achieves delightful performance.

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Acknowledgements

This work is supported by Project NSFC (61602381, 61501372, and 61672428), China Postdoctoral Science Foundation (2017M613187 and 2017M613186), and Natural Science Basis Research Plan in Shaanxi Province of China (2017JM6074).

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Authors and Affiliations

  1. Northwest University, No. 1 Xuefu Avenue, Guodu Education Technology Industrial Zone, Chang’an District, Xi’an, China

    Qing Wang, Xiaoyan Yin, Jun Tan, Tianzhang Xing, Jinping Niu & Dingyi Fang

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  1. Qing Wang
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  2. Xiaoyan Yin
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  3. Jun Tan
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  4. Tianzhang Xing
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  5. Jinping Niu
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Correspondence to Tianzhang Xing.

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Wang, Q., Yin, X., Tan, J. et al. DTransfer: extremely low cost localization irrelevant to targets and regions for activity recognition. Pers Ubiquit Comput 23, 3–16 (2019). https://doi.org/10.1007/s00779-018-1177-7

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  • DOI: https://doi.org/10.1007/s00779-018-1177-7

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