WiImage: Fine-grained Human Imaging from Commodity WiFi

Abstract

Privacy-preserving wireless-based human imaging technologies attract much attention in academia and industry. They can serve in surveillance, security inspection, and health monitoring, while preventing the privacy leakage from current camera-based surveillance system. However, previous solutions either requires dedicated hardware or costly infrastructure deployment, which hurts their practicality. In this paper, we propose WiImage, a low-cost, instantly-deployed sensing system that can capture a fine-grained human image and infer his contour using ubiquitous WiFi. WiImage is free of pre-training or placing any marker on a user’s body. WiImage consists of two technical components. First, a lightweight multipath resolution algorithm exploit the spatial and temporal correlation of WiFi packets to address the multipath and extract reflected signals from a human body. Second, an imaging algorithm infers the contour of a human from WiFi reflections. We prototype WiImage using offthe-shelf WiFi chips and conduct experiments in several typical indoor settings. The results show that WiImage can recover a representative human figure and use it to identify the user precisely.