A Crowd Counting Method Based on Connected Field Image Generation of CSI Phase Difference
JieMing Yang, MingChen Han, Yun Wu · 2024
In response to the current low efficiency of CSI-based crowd-counting technology and the methods overly focus on debugging neural networks or mining more significant feature extraction methods, making the models complex and unstable in changing environments, the novel crowd-counting method named PhiC-Field is proposed in this paper, which is based on a cross-phase difference image generation technique. Firstly, the multi-antenna CSI subcarrier data is compressed and projected onto an orthogonal sampling field plane in pixel form. Secondly, by performing multi-point calculations, a blurred image reflecting the relationship between the number of people and the CSI subcarrier is obtained while preserving all subcarrier information without complex data preprocessing. This article proposes a neural network adapted to Phic-Field, and experiments in various experimental environments have shown that the accuracy of the model is higher than other methods.