@inproceedings{2934924abb334c4ba4cae93e537e5a12,
title = "Poster abstract: Implications of target diversity for organic device-free localization",
abstract = "Device-free localization (DFL) plays an important role in many applications, such as the intrusion detection. Most traditional DFL systems assume a fixed distribution of the received signal strength (RSS) changes even they are distorted by different types of targets. It inevitably causes the localization to fail if the targets for modeling and testing belong to different categories. We propose a transferring scheme for DFL, which employs a rigorously designed transferring function to transfer the distorted RSS changes across different categories of targets into a latent feature space, where the distributions of the distorted RSS changes from different categories of targets are unified. A benefit of this approach is that the same transferred localization models can be shared by different categories of targets, leading to a substantial reduction of the human efforts. The results of experiments illustrate the efficacy of our transferring scheme.",
author = "Ju Wang and Xiaojiang Chen and Dingyi Fang and Wu, {Chase Qishi} and Tianzhang Xing and Weike Nie",
year = "2014",
doi = "10.1109/IPSN.2014.6846762",
language = "English (US)",
isbn = "9781479931460",
series = "IPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)",
publisher = "IEEE Computer Society",
pages = "279--280",
booktitle = "IPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)",
address = "United States",
note = "13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014 ; Conference date: 15-04-2014 Through 17-04-2014",
}