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research-article

CATFSID: : A few-shot human identification system based on cross-domain adversarial training

Authors:

Zhongcheng Wei,

Jijun ZhaoAuthors Info & Claims

Volume 224, Issue C

Pages 275 - 284

https://doi.org/10.1016/j.comcom.2024.06.014

Published: 01 August 2024 Publication History

Abstract

With the advancement of wireless sensing technology, human identification based on WiFi sensing has garnered significant attention in the fields of human–computer interaction and home security. Despite the initial success of WiFi sensing based human identification when the environment is fixed, the performance of the trained identity sensing model will be severely degraded when applied to unfamiliar environments. In this paper, a cross-domain human identification system (CATFSID) is proposed, which is able to achieve environment migration of trained model using up to 3-shot. CATFSID utilizes a dual adversarial training network, including cross-adversarial training between source and source domain classifiers, and adversarial training between source and target domain discriminators to extract environment-independent identity features. Introducing a method based on pseudo-label prediction, which assigns labels to target domain samples similar to the source domain samples, reduces the distribution bias of identity features between the source and target domains. The experimental results show accuracy of 90.1% and F1-Score of 89.33% when using 3 samples per user in the new environment.

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Cited By

Wei ZChen WNing SLin WLi NLian BSun XZhao J(2025)A Survey on WiFi-based Human Identification: Scenarios, Challenges, and Current SolutionsACM Transactions on Sensor Networks10.1145/370832321:1(1-32)Online publication date: 27-Jan-2025
https://dl.acm.org/doi/10.1145/3708323

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CATFSID: A few-shot human identification system based on cross-domain adversarial training

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Information & Contributors

Information

Published In

cover image Computer Communications

Computer Communications Volume 224, Issue C

Aug 2024

315 pages

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Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 August 2024

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Cited By

Wei ZChen WNing SLin WLi NLian BSun XZhao J(2025)A Survey on WiFi-based Human Identification: Scenarios, Challenges, and Current SolutionsACM Transactions on Sensor Networks10.1145/370832321:1(1-32)Online publication date: 27-Jan-2025
https://dl.acm.org/doi/10.1145/3708323

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