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Found 5 papers, 3 papers with code
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements
Tracking subjects in videos is one of the most widely used functions in camera-based IoT applications such as security surveillance, smart city traffic safety enhancement, vehicle to pedestrian communication and so on.
ViFi-Loc: Multi-modal Pedestrian Localization using GAN with Camera-Phone Correspondences
During inference, it generates refined position estimations based only on pedestrians' phone data that consists of GPS, IMU and FTM.
ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning
We introduce ViFiCon, a self-supervised contrastive learning scheme which uses synchronized information across vision and wireless modalities to perform cross-modal association.
ViTag: Online WiFi Fine Time Measurements Aided Vision-Motion Identity Association in Multi-person Environments
ViTag associates a sequence of vision tracker generated bounding boxes with Inertial Measurement Unit (IMU) data and Wi-Fi Fine Time Measurements (FTM) from smartphones.
Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors
In this paper, we present Vi-Fi, a multi-modal system that leverages a user’s smartphone WiFi Fine Timing Measurements (FTM) and inertial measurement unit (IMU) sensor data to associate the user detected on a camera footage with their corresponding smartphone identifier (e. g. WiFi MAC address).
